Time Wealth as a Determinant of Public Transport Behavior: Empirical Evidence from Japan

Abstract

In low-demand areas, optimizing public transport operations requires strategies that go beyond infrastructure improvements. Among the various influencing factors, time wealth—the perceived freedom and flexibility in managing one’s time—emerges as a critical component in encouraging public transport use. Temporal factors like time cost and scheduling inconvenience often hinder usage, making time-related perceptions essential for effective and inclusive transport strategies. This study investigates time wealth as a component of perceived behavioral control in shaping public transport intention. Using empirical surveys in Japan, factor analysis and structural equation modeling identified three dimensions of time wealth and assessed their influence on behavioral intention. Results show that greater time wealth reduces the perceived difficulty of using public transport, thereby enhancing user intention. Positive attitudes and awareness support effective public transport interventions. While improving accessibility and convenience is important, addressing fare affordability is equally vital. A balanced approach that enhances both the experiential and financial aspects of public transport is crucial for maximizing its utilization. These findings highlight the need for integrated strategies that enhance both temporal and financial aspects to boost public transport use.

1. Introduction

In Japan, public transport faces significant challenges due to declining and aging populations, rural migration, and an aging demographic [1]. These factors create a vicious cycle where declining ridership leads to reduced revenue and resource allocation, further worsening the situation. Despite its essential role in providing daily mobility for students, the elderly, and those unable to drive, maintaining regional public transport services incurs substantial costs. In many countries, including the U.S., European nations, and Taiwan, governments absorb these costs through significant subsidies [2,3]. In contrast, Japan tends to shift this financial burden to passengers’ fare, treating transport services as a self-financing industry rather than a societal infrastructure responsibility. Regardless of who bears the financial burden, there is a pressing need for cost-effective strategies to improve public transport services and increase ridership.

To develop effective strategies, it is crucial to understand the factors that influence public transport use. While demographic and economic variables have traditionally been studied, recent research highlights the growing importance of psychological factors in predicting transport mode choices. Variables such as perceived benefits, personal values, and environmental concern have been widely examined [4,5]. However, attitude–behavior inconsistencies are commonly observed when predicting pro-environmental behaviors [6]. These inconsistencies are partly attributed to the difficulties associated with performing certain behaviors, such as the high inconvenience of using public transport as a substitute for car use [7]. Therefore, incorporating control beliefs is crucial for generating more reliable predictions of behaviors. This has led researchers to draw on models like the Theory of Planned Behavior (TPB), which emphasizes the role of attitudes, subjective norms, and perceived behavioral control (PBC) in shaping intention.

In practice, there is growing recognition of the need to enhance spatiotemporal accessibility and improve the overall travel experience to promote public transport usage. Common interventions—such as increasing service frequency, improving punctuality, and reducing transfer times—aim to reduce objective travel and waiting time. While essential, these strategies are often infrastructure-intensive and financially costly, especially in contexts with declining ridership or constrained budgets. Moreover, they tend to focus on external service attributes—what the system provides—rather than on how users subjectively experience and manage their time during travel. These considerations point toward a broader behavioral concern: beyond minimizing time, it is equally important to enhance users’ sense of temporal control. Conventional improvements may not fully capture or influence this subjective dimension, which is increasingly recognized as a key factor in travel satisfaction and behavioral intention. To address this gap, the present study adapts the concept of time wealth, a more holistic, user-centered perspective on temporal accessibility that extends beyond conventional metrics like travel time savings.

Time wealth refers not only to the amount of time available, but also to how that time is perceived, valued, and controlled by individuals in specific contexts [8]. Unlike conventional time-cost indicators such as journey duration or monetary value of time, time wealth emphasizes qualitative dimensions of time use, including scheduling flexibility, synchronization with daily routines, and autonomy over time-related decisions. These aspects align closely with the cognitive and perceived elements of travel behavior, making time wealth particularly relevant in understanding PBC—a core component of the TPB. While traditional applications of PBC in transport research often focus on access to resources or physical ease of use, time wealth captures individuals’ perceived capacity to manage time effectively within the constraints of public transport. By incorporating temporal autonomy and experiential factors, time wealth offers a more nuanced understanding of PBC—highlighting how perceived control over time, rather than physical accessibility alone, shapes behavioral intention and decision-making in travel behavior.

A growing body of research emphasizes the concept of time wealth as a critical factor shaping human behavior and social activities. While time wealth has been conceptually defined in prior studies, a standardized framework for its operationalization and measurement remains lacking, particularly regarding which dimensions to include and how to assess them empirically. Von Jorck et al. identified five key dimensions of time wealth: tempo, plannability, synchronization, time sovereignty, and free time [9]. Vitrano and Mellquist further developed this concept, highlighting time wealth as a crucial dimension of spatiotemporal accessibility in public transport [10]. They suggest focusing on three critical dimensions in scheduling: chronometric (i.e., whether users can complete their journeys within their available time), synchronization (i.e., whether schedules align with users’ needs), and sovereignty (i.e., whether users can make flexible decisions without being constrained by rigid schedules).

Supporting this line of inquiry, a Dutch study demonstrated that the value of travel time is not solely determined by monetary costs or journey duration, but also by passengers’ subjective experiences of time while traveling [11]. Through case studies of rail passengers, the study explored how on-board conditions affect travelers’ cognitive appraisal of time, highlighting the significance of the travel experience itself [11]. In line with these perspectives, Yamachi et al. employed the concept of time wealth to investigate the effectiveness of a cross-sectoral public space revitalization project at a regional railway station [12]. Their study verified that an improved temporal experience could reduce passengers’ resistance to waiting for a train and, in turn, increase ridership at a deficit-running station.

When users perceive greater control over their time—enabled by flexible, reliable, and well-synchronized transport options—they are more inclined to choose public transport over other modes. In this context, time wealth functions not only as a determinant of user satisfaction but also as a strategic and cost-effective lever for encouraging sustainable mobility. While its relevance is increasingly acknowledged, the influence of time wealth remains underexplored in the transport literature.

This study aims to address the identified gap by examining how time wealth contributes to the intention to use public transport through its role within the TPB. Specifically, time wealth is conceptualized as a subcomponent of PBC, capturing users’ perceived ease and autonomy in managing time when using public transport [13]. The study investigates both its direct effect on behavioral intention and its indirect influence through attitudes and subjective norms. Rather than treating TPB components as independent predictors, we adopt an integrative approach that explores how time-related control may shape intention by influencing attitudes toward public transport and perceptions of normative pressure. By clarifying the temporal aspects embedded within PBC, this research contributes to a more nuanced understanding of how psychological mechanisms underlie transport decisions. Practically, the findings are expected to inform more effective public transport strategies by demonstrating how time-oriented improvement can optimize user experience and enhance ridership through efficient use of limited resources.

1.1. Predicting Public Transport Use: The Theory of Planned Behavior

The TPB model has been suggested as a useful framework for studying the intention to use public transport [14]. It provides a concise framework that explains intended behavior, which is determined by three core constructs: attitudes toward behavior, subjective norm, and perceived behavior control. Attitudes toward behavior refer to the degree of a favorable or unfavorable evaluation toward a behavior [15]. Subjective norm pertains to an individual’s perception of social pressures dictating certain behaviors. Additionally, perceived behavior control encompasses the evaluation of the ease or difficulty of performing the behavior in consideration of internal and external factors.

In the TPB framework, PBC not only directly influences behavioral intention but also moderates the effects of attitudes and subjective norms on intention. This means that individuals’ perceptions of their ability to perform a behavior can enhance or diminish the impact of their attitudes and the perceived social pressures on their intentions [16]. PBC has also been identified as playing a critical role in generating more accurate predictions of real behavior from intentions. Heath and Gifford (2002) employed hierarchical multiple regression to analyze the interaction effects between PBC and the intention to use buses [14]. Their findings revealed that the interaction between intention and PBC explained additional variance in behavior, suggesting that intentions predict actual behavior more effectively when PBC is high.

In the context of public transport behavior, PBC reflects how difficult or easy an individual believes using public transport to be. This perception of difficulty is influenced by an internal assessment of external factors, such as access time, travel time, frequency, reliability, transfer walking, and government incentives [17,18]. Urban design elements can also contribute to these perceptions. For instance, as shown in a recent study on walking behavior in Cairo, street planning and design factors significantly influenced individuals’ perceived ease and willingness to walk, a concept closely related to PBC [19]. While PBC has been extensively studied, it encompasses a wide range of factors, and there is no universally agreed-upon definition or framework outlining its precise scope in transport research. This lack of a clear reference point leaves room for interpretation and variation in how PBC is applied and measured across studies.

Time wealth is conceptualized as a latent psychological construct that relates more directly to the “planned” aspect of behavior than to behavior itself in the context of the TPB. It reflects an individual’s capacity to coordinate and manage time in alignment with external transport schedules, which corresponds to their perceived ability to carry out an intended behavior. Specifically, the three dimensions of time wealth proposed by Vitrano and Mellquist [10]—chronometric fit (can the trip be completed in time?), synchronization (does the schedule align with personal needs?), and sovereignty (is the user in control of timing decisions?)—map onto varying levels of scheduling capability. These dimensions, in turn, reflect users’ perceptions of behavioral control in temporal terms. By framing time wealth in this way, the study positions it as a subcomponent of PBC, offering a time-sensitive interpretation of how planned behavior may be shaped by scheduling constraints.

By positioning time wealth as a subcomponent of PBC, this study integrates it into the TPB framework to assess both the direct and indirect pathways influencing behavioral intention. Higher levels of time wealth are expected to increase the likelihood that positive attitudes and normative pressures translate into actual intention to use public transport, while lower time wealth may constrain this translation by reinforcing perceived behavioral barriers. In this way, time wealth may not only act as a direct predictor of intention but also moderate the effects of attitudinal and normative influences. This framework extends the traditional focus on travel time by incorporating broader temporal perceptions, including travel experience and activity coordination. Through this integration of conceptual theory and empirical analysis, the study attempts to contribute a more comprehensive understanding of the temporal dimensions that shape transport behavior.

1.2. Additional Factors

While the core components of the TPB are widely accepted, it has been suggested that its explanatory power can be enhanced by incorporating additional constructs [20]. In this study, three key factors—travel habits, awareness of subsidy expenditures, and willingness to pay—are included to better explain public transport usage intentions and provide practical insights.

Travel habits play a crucial role in shaping transport choices, as such decisions are often habitual rather than deliberative [21]. Regular use of public transport can establish a “scripted choice”, making it the default mode of travel. Conversely, individuals with entrenched car usage habits may find it difficult to switch to public transport due to deeply ingrained preferences. The influence of habits on travel behavior has been empirically validated [22,23]. Given their pivotal role in transport decisions, travel habits are integrated into the model to enhance its explanatory power and provide more comprehensive insights.

In addition, public transportation subsidies are often introduced to improve affordability and promote fairness, particularly for low-income groups [24,25]. There is quantitative evidence of their positive effects on actual ridership [26]. Awareness of these subsidies can shape users’ perceptions of public transport and influence their intentions to use and pay for the service. Drevs et al. found that when users are informed about subsidies, their willingness to pay increases due to concerns about fairness [27]. Despite the importance of this factor in developing self-sustaining public transport services, research on how subsidy awareness impacts user behavior remains limited, leaving a gap that this study aims to address.

1.3. The Hypothesized Model

Figure 1 illustrates the hypothesized expanded TPB model, which builds upon the core factors of the TPB and includes additional elements to better reflect real-world policies and contribute to the literature. The additional factors considered in this model are travel habits, awareness of subsidy expenditure, and willingness to pay.

Hypotheses H1 through H5 are derived from the conventional TPB model. It is anticipated that positive attitudes will enhance awareness of subsidy expenditure (H6), which in turn will increase the intention to use public transport (H7) and affect the willingness to pay for it (H8). These hypotheses are informed by Drevs et al. [27], who found that access to information about public subsidies can lead to crowding-in effects, where increased willingness to pay arises from fairness concerns, as well as crowding-out effects, which are driven by worries about double financing and free-riding. Travel habits have been previously shown to significantly influence the intention to use public transport [23], leading to the formulation of Hypotheses H9 and H10. Additionally, this study explores whether improved time wealth can significantly impact frequent users’ willingness to pay and their intention to use public transport more frequently, with Hypotheses H11 and H12 addressing these effects.

2. Materials and Methods

2.1. Study Site and Context

Kagawa Prefecture, located on the island of Shikoku in Japan, has a population of approximately 916 thousand (as of 1 December 2024) and covers an area of 1877 square kilometers [28,29]. Kagawa Prefecture is situated on the coast of the Seto Inland Sea, across from Okayama Prefecture on Japan’s main island, and is connected by the Great Seto Bridge. Takamatsu, the capital and largest city of Kagawa, serves as the economic and administrative hub of the prefecture. Kagawa also includes Shodoshima, the second-largest island in the Seto Inland Sea. The Sanuki Mountains define the prefecture’s southern border with Tokushima Prefecture. Besides the Takamatsu and Shodoshima areas, Kagawa is divided into three administrative regions: the eastern, central, and western Sanuki areas (Figure 2).

The public transport in Kagawa Prefecture is served by two primary rail networks in addition to the bus services: the JR Shikoku Railway and the Kotohira Electric Railway, known locally as Kotoden. The JR system plays a crucial role in both intercity and local travel within Kagawa, connecting Takamatsu to major cities and the surrounding regions. In addition, the Kotoden rail system offers a vital public transit service within Kagawa, connecting urban areas like Takamatsu with smaller towns and rural regions. This rail network plays a significant role in daily commuting, offering frequent services and serving as a more localized alternative to the JR network.

Kagawa Prefecture has seen a decline in the use of public transport over the years. In 2000, public transport accounted for 9.1% of all travel, with railways contributing 7.7% and buses 1.4%. Walking and cycling made up 21.8%, while motor vehicles dominated with 66.6%. By 2020, the modal share of public transport had decreased to 8.3%, with railways at 7.0% and buses at 1.3%. The share of walking and cycling fell to 17.4%, whereas motor vehicles increased to 70.8% [30].

Along with the ongoing decline in population and the increase in an aging society, the COVID-19 pandemic has caused a significant drop in public transport use in Kagawa Prefecture. Many residents now use public transport infrequently or not at all. As the population continues to age and birthrates decline, there is expected to be a further reduction in long-distance travel, such as commuting and school trips, which may make the situation for major transport lines even more challenging. To address these issues, Kagawa city planners are making efforts in developing a sustainable public transport network throughout the prefecture, with a focus on improving convenience and connectivity among the system.

2.2. Data Collection and Sample Profile

A questionnaire survey was conducted to explore residents’ daily transport habits and their satisfaction with current public transport services. The goal was to identify issues and potential solutions to existing challenges. The data were collected by the local government of Kagawa Prefecture, and the authors collaborated with them on conceptualization, questionnaire design, and data analysis. The survey was conducted from July to September 2024. To ensure broad coverage across different regions and age groups, questionnaires were distributed through various channels: online via a mobile company (n = 1382) and local high schools (n = 543), and as paper surveys through mail targeting older generations (n = 500). A total of 2425 responses were collected.

Table 1. Sample profile.

Characteristics	Sample Size (n = 2425)	Percentage (%)
Gender (n = 2406)
Male	1180	49.1
Female	1202	49.9
Prefer not to answer	24	1.1
Age (n = 2421)
15–19	543	22.4
20–29	34	1.4
30–39	113	4.7
40–49	327	13.5
50–59	511	21.1
60–69	399	16.4
70–79	319	13.2
More than 80	175	7.3
Residential area (n = 2332)
Takamatsu area	506	21.7
Eastern Sanuki area	469	20.1
Central Sanuki area	529	22.7
Western Sanuki area	497	21.3
Shodoshima area	331	14.2
Driver’s license ownership (n = 2416)
Has driver’s license	1631	67.5
Has a motorcycle license only	65	2.7
License returned, no longer held	85	3.5
Never had a license	635	26.3
Household car ownership (n = 2399)
Have a car that can be freely used	1459	60.8
Shared within the household	153	6.4
Car at home, not for my use	655	27.3
No car at home	132	5.5
Pick-up and drop-off (n = 2308)
Has someone to ask for rides freely	1500	65.0
No one to ask for rides freely	808	35.0

Note: Bold italics indicate the category labels of survey items while the plain text beneath them represents response options.

presents the sample profile.

Among the sample, high school students account for 22.4% of the respondents, those in their 20s to 60s account for approximately 40%, and respondents aged 60 and above also represent around 40% of the total. The gender ratio of respondents is nearly equal between males (49.1%) and females (49.9%). Regionally, respondents from the Shodoshima area represent 14.2%, while other regions each account for about 20%. Approximately 70% of respondents hold a driver’s license, while around 30% either do not have a license or have returned it. Over 90% of households own a private car, with 5.5% of households having no car at home. About 30% of individuals live in households with a car but are unable to use it. 35.0% of respondents reported that they have no one they can ask for rides without feeling like a burden.

2.3. Questionnaire Design

The questionnaire comprised three sections: socioeconomics and travel habits, desired improvements for public transport services, and perceptions and attitudes toward public transport operations.

The first section collected data on participants’ socioeconomic characteristics, including gender, age, and the availability of vehicles in their households, as well as their travel behavior habits, such as the frequency of use of different transport modes.

The second section focused on desired improvements in public transport services, emphasizing aspects related to spatiotemporal accessibility. These items are suggested by the established literature but have been adapted to better fit the specific context of this study. This included timetable schedules, information clarity, connections with other modes of transport, punctuality, travel time, and the comfort of waiting areas [9,10]. Items such as the acquisition of new and comfortable vehicles or increased service frequency were excluded from this study due to their high cost and implementation challenges in a real-world context. In this section, respondents were asked to select up to three desired improvements for JR railway, Kotoden, and bus services, respectively. In the data analysis, the responses were coded in a binary format.

The final section examined the social significance of public transport. It evaluated residents’ attitudes and awareness regarding public transport operations, including their level of interest (Question: “To what extent are you interested in public transport?”), their knowledge of operational conditions and annual subsidies (Question: “Public transport is an essential means of mobility for elderly individuals, children, students, and those without driving licenses. To support these services, local governments provide subsidies. Were you aware of this? In the fiscal year 2022, the total subsidies for railways, buses, and passenger ships from the prefecture amounted to approximately 480 million JPY annually, or about 503 JPY per resident”), and their opinions on whether administrative agencies should support the maintenance of local public transport (Question: “Please share your thoughts on whether administrative agencies should provide support to maintain local public transport”). The questions regarding social support and subsidy awareness are inspired by Drevs et al. [27] and have been adapted to reflect real-world conditions.

Additionally, the study investigated residents’ perceived personal benefits (6 items) and social benefits (3 items) of public transport. Perceived personal benefits reflect individuals’ attitudes toward the service, while perceived social benefits align with subjective norms, particularly when social pressure corresponds with public or environmental benefits. While these items are primarily based on the review by Anciaes and Alhassan [31], several were suggested by this study to fit the specific context. Following the presentation of the benefits of public transport, respondents’ intentions were assessed with the question: “Do you plan to use public transport at least once a day in the future, or increase the number of days you currently use it?”

2.4. Data Analysis

Structural equation modeling (SEM) with the maximum likelihood estimates was employed to address a series of interrelated dependence relationships among latent variables and between latent constructs. The data analysis followed a two-stage approach. Before proceeding with the hypotheses verification, Exploratory Factor Analysis (EFA) with binary items was employed to uncover the underlying dimensions of respondents’ preferences for enhancing public transport services. EFA was conducted using a tetrachoric correlation matrix to account for the binary nature of the survey items [32]. Tetrachoric correlations estimate the relationships between latent continuous variables underlying binary responses, providing a more accurate basis for factor extraction than Pearson correlations in this context [33]. Factor extraction was performed using maximum likelihood estimation with varimax rotation. The questionnaire included various items related to desired policies aimed at improving the spatiotemporal accessibility and experience of using public transport. We hypothesized that these preferences are influenced by several latent variables corresponding to different dimensions of time wealth [8,10]. EFA was used to reveal the structure of these preferences and to assess whether the hypothesized dimensions correspond to the observed data.

The hypothesized model was subsequently tested in the second stage. The SEM fit indices used in this study included the comparative fit index (CFI), the Tucker–Lewis index (TLI), the adjusted goodness-of-fit index (AGFI), and the root mean square of approximation (RMSEA). These indices except RMSEA are greater than 0.9, indicating a good model fit [34]. A value of RMSEA up to 0.08 is considered reasonable [35].

Initially, a general hypothesized model was proposed to test established hypotheses from the literature. This model provided a foundational understanding of the key factors influencing public transport use. However, to gain a more comprehensive understanding of real-world dynamics and enhance the relevance of the findings for practical policy-making, additional factors such as geographical and socioeconomic characteristics were incorporated into the model. This expanded model aims to address the complexities and variances in public transport use across different contexts. By integrating these factors, the study enhances its ability to inform and support evidence-based policy analysis and recommendations.

Additionally, effect decomposition analysis was employed to help in understand the effects of various factors on a particular outcome. This method involves breaking down the overall effect into distinct components to evaluate the contribution of each factor. By isolating and examining these components, we can better understand the relative importance of different variables and their interactions. Particularly, this study investigated the contribution of each factor to the intention to use public transport.

3. Results and Discussions

3.1. Descriptive Statistics

3.1.1. Travel Habits and Desired Improvements in Public Transport

Figure 3 illustrates the travel habits of the respondents. As a key intercity mode connecting the central city of Takamatsu with surrounding areas, JR railway is used at least once a week by 9.3% of respondents, while approximately 70% of respondents report infrequent use of JR. In contrast, Kotoden, which serves as a local railway connecting Takamatsu with nearby towns and rural areas, is used at least once a week by only 3.5% of respondents, with around 80% indicating that they do not use this service. Similarly, bus services show a comparable pattern, with 4.5% of respondents using buses at least once a week, while over 80% report minimal to no use of this mode of transport.

Overall, the results reflect a low frequency of use for all three modes of public transport among respondents, highlighting potential issues with accessibility or service attractiveness that may need to be addressed to increase usage.

Table 2. Desired improvements in public transport (select up to three options).

Items		JR	Kotoden	Bus
Sample size		2232	2205	2241
IM1	Convenient schedules that match daily routines	16.8%	10.2%	18.0%
IM2	Clear and consistent scheduling with regular intervals	8.6%	4.9%	7.6%
IM3	Make service operation information clearer	6.5%	4.5%	10.2%
IM4	Reduce travel time	4.5%	2.5%	2.9%
IM5	Ensure timely arrivals (Punctuality)	3.9%	2.0%	8.1%
IM6	Improve connections with other transport modes	16.4%	13.5%	10.4%
IM7	Ensure waiting areas to make waiting time more comfortable	6.6%	4.9%	4.5%
IM8	Reduce fares	31.3%	21.8%	13.5%
IM9	Make it easier to purchase tickets and pay fares	6.5%	5.4%	3.7%
IM10	Change bus service routes	-	-	6.7%
IM11	Reduce the distance to the bus boarding area	-	-	6.8%

Note: Cells with background color indicate response options that received relatively higher selection rates.

presents the desired improvements for each service. Respondents were asked to select up to three options that best reflect their opinions. If they were not familiar with a service, they could choose the “not sure” option. The results indicate that similar issues are urgently desired across all three services. These issues include providing convenient schedules that align with daily routines, improving connections with other transport modes, and reducing fares. Additionally, approximately 10% of respondents requested clearer service operation information for the bus services.

3.1.2. Attitudes and Awareness Regarding Public Transport Operations

Approximately 60% of respondents demonstrated positive attitudes toward public transport, with 19.5% indicating they are “very interested” and 41.9% being “somewhat interested”. The remaining 40% expressed lower levels of interest, with 29.3% being “not very interested” and 9.4% “not interested at all”. When asked about their awareness of public transport maintenance funding, 30.9% of respondents were aware of the subsidies provided, while 69.1% were not.

Regarding views on government support for public transport, 36.1% of respondents felt that “public transport services should be enhanced and maintained even if it requires increasing financial expenditure”. In contrast, 55.9% believed that “efforts should be made to enhance efficiency to maintain public transport services within the current level of financial expenditure”, and 7.9% felt that “financial expenditure should be reduced even if it results in a decline in the level of services”. These results suggest a generally supportive attitude toward public transport, with a notable preference for maintaining or improving services through enhanced efficiency rather than increased expenditure.

3.1.3. Perceived Benefits of Using Public Transport

Table 3. Perceived benefits of using public transport.

Items		Percentage
PB1	Increased opportunities for exercise, which can be effective for weight loss	11.6%
PB2	Ability to freely engage in activities such as reading, studying, playing games, napping, or conversing with friends while traveling	12.5%
PB3	Increased walking distance to and from stations or bus stops, and using stairs, which can reduce medical expenses	5.6%
PB4	Reduction in vehicle maintenance costs due to decreased car usage	11.0%
PB5	Public transport is environmentally friendly, reducing CO2 emissions and contributing to the prevention of global warming	16.6%
PB6	Fewer cars on the road, resulting in less traffic congestion	13.1%
PB7	Ability to return home after drinking or enjoy drinks with family without worrying about transport	7.1%
PB8	No need to worry about arranging transport for yourself or family members going out for drinks	6.2%
PB9	Using public transport can stimulate commercial activity in central areas and other shopping facilities	16.3%

Note: Cells with background color indicate response options that received relatively higher selection rates among participants.

presents various benefits of using public transport. Respondents were asked to select the one benefit they found most appealing. The most frequently chosen options were PB5: “Contributing to the prevention of global warming”, PB6: “Contributing to alleviating traffic congestion”, and PB9: “Stimulating commercial activity in the area”. These options reflect subjective norms, emphasizing the social benefits of public transport. The respondents’ selections highlight their perceptions of the positive societal impact of using public transport.

3.2. Hypotheses Testing

3.2.1. Results of Exploratory Factor Analysis

The resulting factor loadings indicated how strongly each item was associated with the identified factors. Items with higher loadings on a given factor were considered to be more representative of that factor. In this study, items with high factor loadings were grouped together to form distinct dimensions of desired public transport improvements.

Table 4. Dimensions of time wealth identified through exploratory factor analysis.

Factor Loadings		Dimension 1	Dimension 2	Dimension 3
JR1	Convenient schedules that match daily routines	0.98	0.18	−0.01
JR2	Clear and consistent scheduling with regular intervals	0.31	−0.19	0.34
JR6	Improve connections with other transport modes	0.24	−0.10	0.24
JR4	Reduce travel time	0.01	0.44	−0.09
JR5	Ensure timely arrivals (Punctuality)	0.00	0.79	0.10
JR3	Make train operation information clearer	0.13	0.04	0.68
JR7	Ensure waiting areas to make waiting time more comfortable	−0.03	0.00	0.39
Multiple Dimensions of Time Wealth		Synchronization	Chronometric	Sovereignty
SS loadings		1.13	0.90	0.81
Proportion variances		0.16	0.13	0.12
Cumulative variances		0.16	0.29	0.41
Proportion explained		0.40	0.32	0.28

presents the results of the exploratory factor analysis (EFA), categorizing desired improvements for JR railway services. Based on the literature [10], the three categorized dimensions are named as follows:

Factor loadings of ≥0.40 are generally considered meaningful for interpretability in EFA [34]. The three-factor model explained a total of 41% of the variance, which is modest but acceptable for behavioral and social science research, where explained variance of 40–60% is typically considered sufficient [34]. Model fit statistics indicated a good overall fit: RMSR = 0.01, RMSEA = 0.043 (90% CI: 0.025–0.065), and Tucker–Lewis Index (TLI) = 0.926. The significant Bartlett’s test of sphericity (χ² = 16.71, p < 0.001) supports the presence of an underlying factor structure. Additionally, the fit based on off-diagonal values was 0.99, indicating excellent reproduction of the observed correlation matrix. Taken together, these indices support the adequacy of the three-factor solution.

The synchronization dimension underscores the significance of aligning public transport schedules with users’ daily routines and ensuring consistency in service timing. This dimension highlights that users value coordinated and predictable transit services that seamlessly integrate into their everyday lives. It emphasizes the need for schedules that are well-aligned with daily activities and maintain regular intervals to support reliable commuting experiences.

The chronometric dimension emphasizes the efficiency of the public transport system. It focuses on minimizing travel time and ensuring punctuality, reflecting the importance of swift and reliable services. This dimension suggests that respondents prioritize transport services that facilitate prompt arrivals at their destinations without undue time expenditure. Efficient travel and timely arrivals are critical factors in enhancing user satisfaction.

The sovereignty dimension pertains to the quality of information and comfort associated with public transport. It stresses the need for clear and accessible operational information as well as enhanced amenities in waiting areas. This dimension highlights the importance of users’ ability to manage their travel experience. By improving these aspects, the dimension aims to contribute to a more pleasant and stress-free transit experience.

3.2.2. Estimated Hypothesized Model

Figure 4 presents the estimated model with standardized path coefficients and significance levels. The model demonstrates an acceptable fit with the sample data, as evidenced by the goodness-of-fit indices (CFI = 0.924, GFI = 0.976, AGFI = 0.947, RMSEA = 0.067, and SRMR = 0.034). All twelve hypotheses in the model were empirically supported. Travel habits and willingness to pay in Figure 1 were represented by frequency of use and intention to increase use with lower fares, respectively.

The model demonstrated varying levels of explanatory power across the endogenous variables. The model accounted for a substantial proportion of variance in the three dimensions of time wealth: synchronization (R² = 0.72), chronometric (R² = 0.46), and sovereignty (R² = 0.25), indicating a strong to moderate fit between the latent construct and its observed indicators. The second-order latent variable of time wealth itself showed a modest explained variance (R² = 0.14), which is reasonable for an abstract, multidimensional construct. In contrast, the explained variance for behavioral intention (R² = 0.20) was moderate, and values for related attitudinal and normative constructs—such as attitude (R² = 0.09), awareness of subsidies expenditures (R² = 0.05), and subjective norm (R² = 0.01)—were lower. These results are consistent with prior behavioral research, where explained variance tends to be lower for single-item or indirect attitudinal indicators, particularly when incorporating new psychological variables. Overall, the model highlights areas for further refinement in future research. While the explanatory power of some variables is modest, the overall model fit is acceptable, supporting the structural coherence of the proposed framework and providing a foundation for future theoretical development.

Time wealth, conceptualized as a subcomponent of perceived behavioral control (PBC), had a significant and positive impact on both attitudes (β = 0.30, p < 0.001) and intention to use public transport (β = 0.08, p < 0.01). Conversely, it demonstrated a significant but weak negative effect on subjective norms (β = −0.09, p < 0.001). Notably, while PBC directly affects behavioral intention, time wealth serves as an underlying antecedent by influencing both attitudes and subjective norms.

Attitude positively affected intention (β = 0.36, p < 0.001), while subjective norms were found to have a small but negative effect on intention (ß = −0.06). This result contrasts with traditional TPB findings, where subjective norms typically exert a positive influence on intention. One possible interpretation is that individuals with greater awareness of the societal value of public transport may also hold higher expectations for service quality. In the context of small- to medium-sized cities—with populations ranging from several thousand to approximately 400,000—public transport systems often operate at a lower level of service. As a result, this heightened awareness may lead to dissatisfaction or reduced intention to use such services. In such cases, a strong belief in the social value of public transport does not necessarily translate into usage intention when perceived service adequacy is lacking. This interpretation aligns with prior research suggesting that improvements in public transport service quality can trigger modal shift behavior, particularly among individuals with strong subjective norms [36]. This implies that subjective norms may exert conditional influence, becoming more behaviorally meaningful when supported by structural improvements in transport systems.

The frequency of public transport use was positively correlated with time wealth (β = 0.37, p < 0.001). Both the frequency of use (β = 0.08, p < 0.001) and time wealth (β = 0.18, p < 0.001) were significantly associated with the reported likelihood of increased usage if fares were reduced. These findings suggest that greater time wealth may be linked to a higher intention to use public transport. This supports the interpretation that usability—captured here as time wealth—may play a more prominent role in shaping behavioral intentions than fare considerations alone. The results highlight the potential value of improving time-related features to encourage greater public transport usage.

Furthermore, attitudes had a significant positive effect on awareness of subsidy expenditure (β = 0.21, p < 0.001). This awareness positively affected the intention to use public transport (β = 0.05, p < 0.05) while negatively affecting the desire for lower fares. This indicates that improving awareness of public transport subsidies is crucial for enhancing user intention and understanding fare structures. This finding is supported by research from Germany [27], which observed a crowding-in effect on willingness to pay due to increased information about public subsidies, highlighting concerns about fairness.

3.3. Expanded Models for Policy Analysis

To provide a more comprehensive understanding of public transport behavior, the expanded models incorporated geographical and socioeconomic factors, including age group and residential area. Additionally, variables such as perceived benefits and the perceived necessity of administrative support were included to capture broader contextual influences. The structural relationship of perceived benefits is grounded in the TPB and conceptually aligns with attitudinal variables. In contrast, the perceived necessity of administrative support is modeled as an outcome variable, influenced by favorable attitudes toward public transport and awareness of subsidy expenditures. These additions allowed for comparisons across different public transport modes.

Figure 5 presents the estimated results for JR, Figure 6 for Kotoden, and Figure 7 for buses. The layers in the figure are organized around the concept of discretionary freedom, which represents individuals’ ability to make choices and decisions based on their personal preferences and judgments, without undue external constraints. In the context of public transport, the sovereignty dimension supports significant discretionary freedom, allowing users to manage their time according to their needs and preferences. This is complemented by the dimensions of synchronization and chronometric dimensions.

The analysis revealed consistent patterns across the three modes. Older age groups generally exhibited a positive attitude towards public transport, with significant correlations for JR (β = 0.26, p < 0.001), Kotoden (β = 0.26, p < 0.001), and buses (β = 0.12, p < 0.05). Conversely, a negative correlation was observed between age group and frequency of use for JR (β = −0.43, p < 0.001), Kotoden (β = −0.25, p < 0.001), and buses (β = −0.29, p < 0.001), indicating a higher reliance on public transport among younger users, such as high school students. This finding is corroborated by the negative correlation between age groups and the perceived need for administrative support in maintaining public transport services.

Geographical factors reflected actual usage patterns effectively. Residents in Sanuki areas, encompassing local towns and rural areas, showed higher reliance on private cars, which resulted in significant negative correlations with the frequency of use across all three public transport modes. In contrast, Takamatsu residents demonstrated a higher usage frequency of the intracity rail service Kotoden and a lower frequency of bus usage.

Attitude positively influenced support for increased administrative assistance for public transport, with this correlation being consistent across all models (β = 0.30, p < 0.001). Moreover, awareness of subsidy expenditure also significantly positively affected residents’ support for administrative support (β = 0.30, p < 0.001). These findings underscore the importance of both positive attitudes and informed awareness in garnering support for enhanced administrative measures in public transport. This suggests that strategies aimed at improving public perceptions and increasing awareness of financial support mechanisms can effectively strengthen backing for necessary administrative interventions.

Perceived benefits, introduced as an attitudinal variable, showed positive correlations with time wealth, particularly for JR. Unlike subjective norms, which focus on environmental and social benefits, perceived benefits—including health improvements and cost savings (PB1, PB3, PB4 in Table 3)—had a stronger positive effect on the intention to use public transport. This finding supports previous research suggesting that attitudinal variables have a greater influence on user intention than normative values [37].

3.4. Effect Decomposition Analysis

Effect decomposition analysis was employed to dissect and analyze the influence of various factors on the intention to use public transport. In this analysis, particular attention was given to attitudinal variables, time wealth as a subcomponent of PBC, subjective norms, as well as geographical and socioeconomic characteristics.

As shown in Figure 8 (left), the direct effects of each factor on intention reveal that attitude and time wealth have the most significant impacts. Perceived benefits, considered a component of attitude, were aggregated with attitude to assess the overall effects of attitudinal variables on intention. Additionally, improving awareness of subsidies for public transport is interpreted as enhancing social norms broadly, which, in turn, increases intention; this effect was integrated into the subjective norm category.

Figure 8 (right) compares the effects of the core Theory of Planned Behavior (TPB) factors—attitudinal variables, subjective norm, and PBC (i.e., time wealth in this study)—on intention. Attitudinal variables exert the greatest influence on intention, followed by time wealth and subjective norm. Additionally, geographical factors, including the Takamatsu and Sanuki areas, have positive direct effects on intention relative to the reference area of Shodoshima.

Figure 9 illustrates the cumulative effects of each factor on behavioral intention, incorporating both direct and indirect effects. The analysis reveals that PBC has the most significant impact on intention, followed by attitudinal variables and subjective norms. These findings corroborate the results presented in Section 3.2.2, demonstrating that time wealth functions as an underlying antecedent in the formation of behavioral intention by influencing both attitudinal and normative components. Specifically, time wealth appears to be linked to behavioral intention both directly and indirectly through its associations with attitudes and subjective norms. This insight contributes to a more nuanced understanding of how the TPB can be applied in travel behavior research, particularly by highlighting the role of temporal perceptions in shaping intention

4. Conclusions

This study addresses the lack of conceptual clarity in the definition and operationalization of perceived behavioral control (PBC) in public transport research by introducing time wealth as a core component of PBC. Drawing on empirical survey data from Japan, we conceptualize and validate time wealth through exploratory factor analysis, identifying three key dimensions grounded in the literature. These dimensions capture critical time-related aspects of public transport that shape user intentions, such as scheduling flexibility and temporal alignment with individual needs.

The findings of this study offer several theoretical implications for understanding public transport behavior. Specifically, they suggest that enhancing time wealth reflects a lower perceived difficulty of using public transport, as it captures the alleviation of time-related constraints and improvements in the overall temporal experience. This study contributes a clearer, behaviorally grounded framework for public transport research by reconceptualizing PBC to include time-related factors, thereby strengthening its theoretical relevance within the Theory of Planned Behavior (TPB).

Building on this framework, we further examine how time wealth interacts with other key components of the TPB. The interplay between subjective norms, attitudes, and PBC in shaping the intention to use public transport can be understood as a decision-making process, rather than as a linear influence of independent determinants. Subjective norms influence whether individuals feel social pressure to adopt public transport, while attitudes relate to perceived benefits and preferences. PBC—reconceptualized as time wealth—reflects the perceived ease or difficulty of using the service. Our results show that time wealth, encompassing both spatiotemporal accessibility and temporal satisfaction, plays a critical role in shaping intention. Notably, its cumulative effect exceeds that of attitudinal factors alone, suggesting that conventional TPB models may underestimate the influence of temporal experience. These findings call for a more integrative behavioral modeling approach that explicitly incorporates interaction effects among core psychological constructs.

In addition, this study proposes an expanded TPB framework by incorporating supplementary behavioral constructs such as travel habits, awareness of subsidy expenditures, and willingness to pay. These extensions underscore the theoretical value of integrating individual-level financial and habitual dimensions into intention modeling. Importantly, the results indicate a positive association between favorable attitudes, awareness of transport subsidies, and both behavioral intention and public support for transit initiatives. This highlights the relevance of attitudinal and cognitive factors not only in shaping intention, but also in reinforcing structural policy mechanisms. Altogether, the study advances the theoretical understanding of transport mode choice by linking psychological constructs with temporal and policy-relevant considerations.

The study also highlights policy implications. Time-related service features have varying effects on user intention across different travel modes. For rail systems, the chronometric and synchronization dimensions have a stronger influence on user intention. Practical improvements typically focus on reducing travel time, ensuring punctuality, and improving intermodal connections. However, operators can further optimize services by offering patterned timetables or aligning schedules with users’ daily routines, simplifying planning, and making public transport easier to integrate into daily life. Bus users, on the other hand, have different service needs. Sovereignty, which includes punctuality, clear information, and comfortable waiting areas, plays a key role in enhancing time wealth. Notably, many bus stops lack adequate waiting areas, highlighting the need to reduce waiting times to improve users’ autonomy over their time. Similarly to rail services, scheduling strategies like patterned timetables are also seen as desirable improvements for bus users.

Prior studies have developed transit assignment models and optimization techniques from a systems and simulation perspective [38,39], offering tools for understanding how service frequency and stop placement affect network performance and accessibility. This study offers a complementary behavioral perspective by emphasizing the importance of subjective time perception and temporal control in shaping public transport intention—providing insights that extend beyond operational planning to inform more user-centered service design.

Limitations and Future Research Directions

This study acknowledges several limitations and outlines corresponding directions for future research. First, the use of binary-coded items instead of multi-point Likert scales may reduce psychometric sensitivity and limit the ability to capture nuanced variations in participant responses. This simplification was a deliberate trade-off to ensure higher response rates and reduced cognitive load in a large-scale, self-administered survey. To mitigate the impact on construct validity, factor analysis was conducted using a tetrachoric correlation matrix, which is appropriate for dichotomous items and allows estimation of the underlying latent structure. While this approach addresses some concerns related to binary data, future research may benefit from using Likert-type response formats to enhance measurement precision and validity.

Second, the use of a self-administered survey—distributed via both web-based and paper-based formats—without in-person facilitation may have introduced self-selection bias. Individuals with a greater interest in transport issues may have been more likely to participate. Future studies should consider employing stratified random sampling or weighting techniques to enhance representativeness.

Third, the reliance on cross-sectional data limits the ability to infer causality and track behavioral changes over time, particularly regarding actual shifts in public transport usage. Future research could address these limitations by conducting longitudinal studies to better capture causal relationships and by testing time wealth interventions through experimental designs, such as pre- and post-intervention studies.

Fourth, the sample includes a relatively high proportion of high school students (22.4%), which may affect the generalizability of the findings to the broader adult population. While students are a relevant user group in transport policy, future research could apply stratified sampling or subgroup analysis, tailored to the study context, to better account for age-related differences in behavioral patterns.

Lastly, while this study offers an initial conceptualization and empirical validation of time wealth as a latent construct, it should be noted that time wealth may not be experienced uniformly across social groups. Factors such as age, occupation, and caregiving responsibilities likely shape time-related constraints in different ways. This research provides a general framework that serves as a foundation for future theoretical development. Further studies could explore how time wealth varies across demographic and socioeconomic groups to better inform inclusive transport policy and interventions.