The Workplace Dilemma: Examining the Effects of Work-Related Constraints on Travel Decision-Making

Abstract

Work-related constraints significantly hinder individuals’ ability to engage in leisure travel, impacting mental health and work–life balance. This study investigates the influence of work-related travel constraints on travel intentions using the Theory of Planned Behavior (TPB) as a framework. By integrating work-related constraints into the TPB model, this study examines how these barriers shape attitudes, subjective norms, and perceived behavioral control, as well as their subsequent impact on travel intentions. Data were collected through an online survey of 274 employed individuals in South Korea and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that work-related travel constraints negatively affect attitudes and perceived behavioral control, which in turn reduce travel intentions. Subjective norms, however, positively influence attitudes and perceived behavioral control, highlighting the critical role of social support in mitigating constraints. Additionally, attitudes mediate the relationship between work-related constraints and travel intentions, as well as between subjective norms and travel intentions. These results emphasize the psychological and structural effects of work-related constraints on leisure travel decisions. The research offers both theoretical and practical insights, advocating for workplace policies and initiatives aimed at enhancing work–life balance and facilitating leisure travel for individuals facing constraints.

1. Introduction

In an era where well-being is recognized as essential, individuals are well aware of the benefits of leisure travel in promoting mental and physical restoration. However, while many aspire to engage in travel for relaxation and personal enrichment, various constraints—both personal and external—can shape their ability to do so (Staffing Industry Analysts, 2024). Among these, work-related constraints play a significant role, influencing not only the frequency and duration of travel but also the ability to fully disconnect (Deloitte, 2024). The expansion of hyperconnectivity, escalating workloads, and workplace cultures that equate dedication with constant availability have made it increasingly difficult for employees to step away from professional obligations. As a result, vacations—once seen as critical for recovery and productivity—are often shortened, postponed, or limited in scope as individuals navigate the competing demands of work and leisure aspirations (Paulise, 2024).

Recent industry findings illustrate the widespread nature of this issue. A 2024 Eagle Hill Consulting survey found that nearly half of employees forgo vacations, citing heavy workloads as the primary reason (Godlen, 2024). Even when time off is taken, the expectation to remain accessible persists—68% of workers continue to perform job-related tasks while on vacation, and 35% feel pressured to stay available to their managers. This trend reflects a deep-rooted structural challenge within modern workplaces, where detachment from work is often perceived as irresponsibility. Consequently, professionals find themselves adjusting their travel plans—whether by reducing trip duration, opting for closer destinations, or integrating work into their vacations—rather than experiencing true disengagement from professional obligations. Addressing this issue is not only a matter of individual choice but a critical challenge requiring organizational and policy-driven solutions to foster a healthier work–life–travel equilibrium.

The growing disruption of work–life balance, where the need for vacations conflicts with work-related constraints, not only limits individuals’ ability to fully experience the benefits of leisure travel but also contributes to negative psychological and professional consequences (Hobfoll, 1989). Leisure travel is widely recognized for its mental health benefits, including stress reduction, enhanced creativity, and increased job satisfaction, which, in turn, improve workplace productivity and long-term career sustainability. Conversely, prolonged exposure to high-pressure work environments without sufficient detachment increases the risk of burnout, reduced job performance, and diminished life satisfaction.

While some attempt to mitigate these constraints through adaptive strategies, such as synchronizing leisure with work schedules or engaging in digital leisure, these efforts often fail to fully compensate for the lack of true psychological detachment from work (Dickinson et al., 2011). The persistent tension between professional obligations and the need for rest underscores an urgent need for organizational and policy-driven solutions to establish clear boundaries between work and leisure. Addressing these challenges is not only vital for enhancing individual well-being but also essential for fostering sustainable workplace productivity in the long term.

As work-related constraints increasingly influence travel behavior, both empirical validation and a stronger theoretical foundation are essential to comprehensively examine their multifaceted impact. Travel constraints, a widely used notion in leisure studies, provide valuable insight into barriers that prevent individuals from engaging in travel (Crawford et al., 1991). Nevertheless, it has been underutilized in understanding occupational travel constraints. While prior research has largely focused on specific populations such as seniors (Kazeminia et al., 2015), individuals with disabilities (Tao et al., 2019), and pet owners (Ying et al., 2021), the distinct barriers faced by working professionals—who must navigate both logistical and psychological constraints—remain inadequately explored. Furthermore, work-related constraints have traditionally been classified under structural barriers, failing to capture their psychological effects, such as stress, workplace guilt, and the pressure to remain professionally available even during vacations (C. C. Chen & Petrick, 2016). Given that these constraints not only restrict travel participation but also reshape how individuals experience vacations, a refined application of travel constraints theory is needed—one that integrates the psychological dimensions of work-related limitations to provide a more comprehensive understanding of their influence on modern travel behavior.

Building on this background, this study examines attitude, subjective norms, and perceived behavioral control as the psychological mechanisms through which work-related travel constraints shape travel intentions, applying the extended Theory of Planned Behavior (TPB) as a guiding framework. TPB provides a structured approach to analyzing intention-driven decision-making; however, its explanatory power is limited, as it assumes that behaviors are primarily driven by rational evaluations of attitudes, subjective norms, and perceived behavioral control (Ajzen, 2002). This assumption does not fully capture the structural and cultural influences that shape decision-making. Moreover, TPB often struggles with the intent–behavior gap, as individuals may intend to travel but face external constraints that prevent them from following through—a notion not reflected in the original TPB model (Ajzen & Fishbein, 1980). To address these limitations, this study extends TPB by integrating work-related constraints as a direct antecedent to its core constructs, recognizing that these constraints do not merely restrict travel participation but actively shape attitudes, subjective norms, and perceived behavioral control. By embedding work-related constraints within extended TPB, this study enhances the model’s predictive accuracy in non-volitional contexts, providing a more comprehensive framework that reflects the interplay between professional obligations and travel decision-making.

This extension of TPB offers a novel theoretical perspective by recognizing that constraints are not just barriers to action but integral components of the decision-making process. While prior research has often viewed travel constraints through the lens of negotiation strategies applying the constraint–effects–mitigation model (Karl et al., 2022), this study directly embeds them within the extended TPB framework, enabling a more comprehensive understanding of their indirect and mediating effects on travel behavior. By shifting the focus from constraints as static limitations to dynamic psychological influences, this study enhances TPB’s explanatory power in constrained travel contexts, bridging the gap between workplace demands and travel decision-making.

The primary objective of this research is to examine how work-related constraints influence key TPB constructs and, consequently, shape travel intentions. Specifically, this study investigates the direct effect of work-related constraints on PBC, the mediating role of attitudes, and the moderating influence of subjective norms in shaping travel behavior. Given that work-related constraints directly impact perceived control over travel decisions, this research provides a nuanced assessment of the cognitive processes underlying constrained travel behavior, offering both theoretical advancements and practical implications for understanding the interplay between professional obligations and travel choices. The remainder of the paper follows the steps outlined in the research process flow chart presented in Figure 1.

2. Literature Review

2.1. Travel Constraints

Travel constraints are factors that hinder or limit individuals’ ability to engage in travel activities, shaping their decisions, preferences, and overall behavior (Mannell & Loucks-Atkinson, 2005). These constraints arise from internal, social, or structural challenges, influencing individuals’ capacity to participate in leisure travel (Karl et al., 2020). Recognizing the impact of these constraints is critical in travel behavior research, as they often lead to reduced travel frequency, postponed plans, or avoidance of specific destinations (Mei & Lantai, 2018). Additionally, constraints can result in emotional outcomes, including frustration, dissatisfaction, and unfulfilled desires.

Travel constraints are frequently conceptualized within the framework of leisure constraints theory, which categorizes them into intrapersonal, interpersonal, and structural dimensions (Crawford et al., 1991; Karl et al., 2022; Kazeminia et al., 2015). This theoretical approach highlights the interplay between psychological barriers, social dynamics, and environmental factors, providing a comprehensive understanding of what prevents individuals from traveling. However, while the framework effectively addresses general travel constraints, it often overlooks context-specific barriers unique to particular populations or situations. Addressing these context-dependent constraints is essential, as they significantly impact leisure travel. Despite their importance, research focusing on these specific barriers remains limited.

Existing research on travel constraints has delved into the challenges faced by specific demographic groups, including seniors, individuals with disabilities, and pet owners. For example, Kazeminia et al. (2015) examined the travel constraints experienced by older adults, identifying barriers such as declining physical health, mobility limitations, and social isolation. These factors interact with structural constraints, such as limited accessibility at destinations and the lack of senior-friendly services, ultimately influencing travel participation and destination choices. Similarly, Tao et al. (2019) focused on individuals with disabilities, emphasizing both structural barriers—such as inadequate infrastructure, inaccessible transportation, and limited accommodation—and intrapersonal constraints, including anxiety about navigating unfamiliar environments and social stigma. Ying et al. (2021) highlighted the constraints faced by pet owners, including restrictions on traveling with pets due to policies at accommodations and transportation services, as well as the added financial and logistical burdens of ensuring pet care during travel.

Although these studies shed light on the constraints specific to these populations, they predominantly rely on the general leisure constraints framework, categorizing barriers into intrapersonal, interpersonal, and structural dimensions without fully addressing the nuanced challenges unique to each group. For instance, while the framework acknowledges structural barriers like accessibility, it often overlooks the complexity of needs specific to certain disabilities, such as sensory impairments or cognitive challenges. Similarly, the emotional and logistical intricacies faced by pet owners, such as the psychological attachment to pets or the need for specialized services, remain underexplored.

Moreover, research in this domain has largely neglected other types of constraints that significantly hinder leisure travel, particularly work-related barriers. These constraints, which stem from professional responsibilities, are often overshadowed by the broader structural category within the leisure constraints framework (Karl et al., 2020). This lack of focused inquiry has limited the understanding of how workplace demands, such as rigid schedules, high workloads, or cultural norms discouraging time off, uniquely impact leisure travel. Exploring these specific constraints is crucial, as they can exert a profound influence on travel frequency, destination choice, and overall participation, often intersecting with other demographic and contextual factors. Addressing these gaps is necessary in providing a more comprehensive and tailored perspective on the diverse barriers to travel faced by different populations and contexts.

2.2. Work-Related Travel Constraints

Work-related constraints refer to challenges imposed by professional responsibilities that restrict individuals’ ability to engage in leisure and vacation activities (M. F. Chen & Tung, 2014). These barriers are embedded in modern workplace demands, including long working hours, inflexible schedules, and expectations of constant connectivity (Tsaur et al., 2012). While underexplored in travel literature, insights from leisure studies reveal work-related constraints as structural and psychological barriers that limit participation in restorative activities (Y. S. Lin et al., 2014). These constraints encompass practical obstacles, such as limited vacation time and unpredictable work schedules, as well as psychological pressures like work-related stress and guilt over taking time away from professional duties (Tsaur & Yen, 2018).

In studies of travel constraints, work-related factors are typically included under the broader category of structural constraints, alongside variables such as limited time, financial restrictions, and family obligations (C. C. Chen & Petrick, 2016; Karl et al., 2022). However, subsuming work-related constraints within the broader category of structural constraints fails to capture their distinct influence. The unique impact of work-related constraints tends to be overshadowed when combined with other structural factors, highlighting the need for a more nuanced understanding of how professional obligations specifically shape leisure and travel behavior.

A related concept is work–leisure conflict (WLC), which emphasizes the inter-role tension between occupational demands and leisure pursuits (Tsaur et al., 2012). Unlike general structural constraints, which focus on time limitations and external barriers, WLC explores how work pressures actively interfere with leisure engagement, resulting in psychological and behavioral conflicts. Past studies have identified two primary directions of WLC: work–leisure conflict (WLC), where job demands reduce an individual’s ability to engage in leisure, and leisure–-work conflict (LWC), where leisure participation interferes with work performance (Y. S. Lin et al., 2014; Tsaur & Yen, 2018).

Several WLC models have been developed to measure the impact of work on leisure choices and well-being. Tsaur et al. (2012) introduced a multidimensional measurement of WLC, categorizing conflicts as time-based, strain-based, or behavior-based. This model provides a structured approach to understanding how work stress reduces leisure participation and satisfaction. Similarly, Y. S. Lin et al. (2014) examined how work–leisure conflict in hospitality employees leads to job burnout, demonstrating that WLC negatively affects leisure satisfaction and psychological well-being. Furthermore, Gao et al. (2019) explored WLC in Taiwan, finding that excessive work hours contribute to life dissatisfaction and that segmentation between work and leisure roles helps mitigate this conflict.

Although these WLC studies provide valuable insights into work–leisure tensions, they do not directly assess how work constraints influence travel behavior within a theoretical decision-making framework. Prior research has primarily focused on the consequences of WLC on well-being and job satisfaction, rather than its role in shaping travel decision-making processes. Moreover, existing WLC models often conceptualize work constraints as general lifestyle pressures, failing to differentiate their role in planned travel decisions. This study addresses this gap by integrating work-related constraints directly into the Theory of Planned Behavior (TPB), treating them as antecedents to attitudes, subjective norms, and perceived behavioral control (PBC), which subsequently influence travel intentions. This theoretical refinement allows for a more precise analysis of the psychological mechanisms that link workplace pressures to constrained travel behavior.

Work-related constraints are multifaceted, influenced by individual and organizational factors and shaped by specific workplace demands. Among these, time scarcity is the most cited constraint, as high workloads and demanding schedules limit discretionary time for vacations (Gao et al., 2019). Irregular schedules, particularly for early-career or hourly workers, further hinder leisure planning, negatively affecting well-being (J. H. Lin et al., 2015). Psychological barriers, such as guilt over taking time off and fear of job insecurity, exacerbate these constraints, discouraging individuals from prioritizing vacations (De Bloom et al., 2010).

Organizational culture intensifies these challenges. Workplaces that discourage taking leave often instill guilt in employees, reducing the likelihood of vacation use (Baker et al., 2022). High-performance environments uphold “ideal worker” norms, prioritizing constant availability and productivity, which further limit opportunities for leisure (Perlow & Porter, 2009). Consequently, work-related constraints shape travel behavior by reducing vacation frequency, prompting shorter, less ambitious trips, and influencing destination preferences toward closer, less resource-intensive options.

Despite their significance, research on work-related travel constraints remains scarce. Tan and Chen (2021) explored how tourists navigate these constraints through the dual-purpose use of smartphones, enabling them to balance work and leisure while enhancing travel experiences (M. F. Chen & Tung, 2014). Their findings highlight variations in travel motivations between first-time and repeat visitors, with first-timers prioritizing relaxation and repeat travelers seeking diverse activities. However, this study’s focus on a specific destination (Hualien) limits its generalizability, and it primarily examines constraints during travel rather than their influence on travel intentions. Other studies have investigated the psychological impacts of work-related constraints. For example, Tan and Li (2021) demonstrated how perceived guilt from taking time off reduces vacation intentions, especially when employees fear damaging their professional standing. Similarly, S. Park and Lehto (2024) examined constraints in bleisure travel, identifying barriers such as time and cost, but their findings are specific to trips combining business and leisure, leaving gaps in understanding leisure travel constraints alone.

2.3. Theory of Planned Behavior (TPB)

The Theory of Planned Behavior (TPB), proposed by Ajzen and Fishbein (1980) is a foundational psychological framework for understanding and predicting human behavior, particularly in contexts involving complex decision-making processes. Building on the earlier Theory of Reasoned Action (TRA), TPB incorporates the construct of perceived behavioral control, which captures individuals’ perceptions of their ability to perform a behavior, making it particularly useful for studying behaviors that are not entirely under volitional control (Erul et al., 2023; Goh & Ritchie, 2011; Quintal et al., 2010). This characteristic has established TPB as a robust framework in fields such as travel behavior research.

The Theory of Planned Behavior (TPB) consists of three primary constructs: attitude toward the behavior, subjective norms, and perceived behavioral control (Ulker-Demirel & Ciftci, 2020). Together, these elements shape behavioral intentions, which are posited to predict actual behavior (Ajzen & Fishbein, 1980). Attitude reflects an individual’s positive or negative evaluation of engaging in a behavior and is influenced by beliefs about the outcomes and their perceived value. For instance, in the context of leisure travel, individuals who associate travel with benefits like relaxation or personal growth tend to develop favorable attitudes toward traveling (Lam & Hsu, 2006). Subjective norms represent the perceived social pressures to perform or avoid a behavior, shaped by beliefs about whether significant others approve or disapprove of the behavior (Ajzen & Fishbein, 1980). For example, professionals who perceive their peers as endorsing vacation-taking for work–life balance may feel encouraged to prioritize leisure travel (Quintal et al., 2010). Perceived behavioral control (PBC) refers to individuals’ perceptions of how easy or difficult it is to perform the behavior, influenced by internal factors, such as skills or knowledge, and external factors, such as financial resources or time availability (Ajzen, 2002). In travel contexts, constraints like high workloads or limited finances can diminish perceived control, reducing travel intentions (Hagger et al., 2002).

Empirical studies based on the TPB framework consistently demonstrate the predictive power of its three core variables for behavior (Chiu et al., 2014). For instance, Liu and Park (2024) explored the influence of metaverse tourism on users’ intentions to visit actual destinations and found that attitude, subjective norms, and perceived behavioral control significantly predicted behavioral intentions. However, research also highlights variability in the relative influence of these predictors. Fu and Zhao (2024) revealed that tourists with favorable attitudes toward eco-friendly travel and strong self-efficacy in adopting sustainable practices are more likely to engage in sustainable tourism, with social norms playing a comparatively minor role. Conversely, some studies suggest that not all TPB constructs equally contribute to predicting behavior. For example, Balıkçıoğlu Dedeoğlu et al. (2022) found that while attitudes toward local food and perceived behavioral control positively influenced tourists’ intentions to consume local food, subjective norms had no significant impact. These findings underscore the nuanced applicability of TPB across diverse contexts, highlighting the importance of examining how its constructs interact in specific behavioral settings.

Despite TPB’s established validity, it bears limitations. One of TPB’s fundamental assumptions is that individuals make rational, intention-driven decisions, but this overlooks the reality of external influences, such as workplace obligations, which limit individuals’ ability to act on their travel intentions. This intent–behavior gap is a critical limitation of TPB, as people may strongly intend to travel but face external constraints that prevent them from following through (Hsu & Huang, 2012). In addition, TPB does not fully account for structural and cultural influences that shape decision-making beyond individual agency. While subjective norms capture peer and social influences, they do not explicitly address institutional constraints, such as workplace norms that discourage time off or promote continuous availability, which are critical in shaping attitudes and perceived behavioral control.

To address the limitations of TPB, including its reliance on rational decision-making assumptions, omission of external structural barriers, and challenges in capturing non-volitional influences, extended TPB models have been developed to incorporate additional constructs, thereby enhancing its predictive and explanatory power. For instance, factors such as perceived constraints, emotional responses, and external facilitators have been integrated into the TPB framework to better reflect the complexities of real-world decision-making (Liu & Park, 2024; Soliman, 2021). Notably, previous studies have extended TPB by integrating technological engagement, environmental considerations, and social influences to account for behavioral variation. For example, Liu and Park (2024) expanded TPB by integrating the Technology Acceptance Model (TAM), positioning TAM variables as antecedents to TPB constructs, thereby bridging gaps between technological engagement and behavioral intention. Similarly, research on work–leisure conflict suggests that occupational obligations do not simply prevent travel but actively shape individuals’ attitudes and control perceptions, reinforcing the need to embed work-related constraints as an antecedent variable within TPB rather than treating them as an external inhibitor.

The extended Theory of Planned Behavior (TPB) model has been extensively applied in tourism research to investigate how attitudes, subjective norms, and perceived behavioral control (PBC) shape travel intentions and actions. For example, studies examining sustainable tourism have revealed that tourists’ positive attitudes toward environmental conservation and their perceived ease of engaging in sustainable practices significantly influence their travel choices (Chiu et al., 2014; Rahman & Reynolds, 2016). Similarly, subjective norms, including societal or peer expectations, have been shown to encourage participation in eco-friendly tourism activities, though their impact is often moderated by cultural and demographic factors (Nguyen et al., 2023).

The TPB framework has also proven effective in understanding travel decision-making in specific contexts. For instance, Han and Kim (2010) utilized the TPB model to study tourists’ intentions to stay at green hotels, demonstrating that PBC factors—such as affordability and convenience—played a critical role in promoting pro-environmental lodging choices. In another application, Mohaidin et al. (2017) explored international travel intentions among students, finding that subjective norms, including family and peer recommendations, were instrumental in shaping their decisions. These applications underscore the model’s versatility in analyzing both psychological and contextual factors across diverse tourism settings.

Constraints have also been integrated into the extended TPB model to further explain individuals’ behaviors in specific contexts. For instance, Shrestha and Burns (2016) incorporated constraints into TPB to study deer hunting behavior, revealing that only PBC emerged as a significant predictor, highlighting the critical role of constraints in shaping participation. Although limited, some studies have employed the extended TPB model to examine travel constraints. S. H. Park et al. (2017) investigated Chinese college students’ intentions to travel to Japan, focusing on the mediating role of travel constraints within TPB. Their findings indicated that travel constraints significantly mediate the relationship between attitude and subjective norms with travel intention, suggesting that constraints diminish the positive effects of favorable attitudes and social norms on travel intentions. Interestingly, this study found that travel constraints did not mediate the relationship between PBC and travel intention, implying that even when individuals perceive control over their decisions, constraints can independently influence their intentions.

However, the number of studies that have explicitly incorporated travel constraints into TPB remains relatively limited, especially when compared to the broader body of constraint research grounded in the constraint–effects–mitigation (CEM) model. The CEM model primarily focuses on how travelers negotiate or mitigate constraints to participate in travel, whereas TPB-based constraint studies aim to examine how constraints shape behavioral intentions. Despite the value of CEM research in understanding constraint negotiation strategies, it does not directly account for how constraints modify cognitive processes within a structured decision-making framework like TPB.

Furthermore, existing TPB-based constraint studies have notable limitations. Many prior studies conceptualize constraints as external inhibitors that limit travel participation but fail to explore their psychological effects within the decision-making process. Most adopt a multidimensional approach (structural, interpersonal, and intrapersonal) derived from general leisure research rather than isolating work-related constraints as a distinct category. For instance, S. H. Park et al. (2017) applied broad leisure constraints without distinguishing how occupational constraints uniquely influence attitudes, subjective norms, and PBC in a professional context. Similarly, Tan and Chen (2021) explored work constraints through the lens of leisure constraint negotiation, examining smartphone use as a coping mechanism rather than investigating the cognitive processes shaping travel intentions within TPB.

Unlike these studies, the present research directly integrates work-related constraints into TPB, treating them as antecedents that shape attitudes, subjective norms, and PBC rather than external barriers or negotiation factors. This approach advances TPB’s application in travel behavior research by offering a more refined understanding of how modern workplace demands influence personal travel decisions. In contrast to previous studies, which tend to either examine work constraints through a general constraint framework or focus on negotiation strategies, this study explicitly positions work-related constraints as a core variable influencing TPB constructs rather than as an external factor that travelers must overcome.

3. Research Model and Hypotheses

The Theory of Planned Behavior (TPB) provides a robust framework for understanding and predicting human behavior by examining the interplay of attitudes, subjective norms, and perceived behavioral control (Ajzen & Fishbein, 1980). Building upon this foundation, the extended TPB model incorporates work-related travel constraints as a preceding variable to the original constructs, offering a nuanced perspective on the determinants of travel intention for constrained travelers. The conceptual model and main hypotheses are depicted in Figure 1.

Work-related travel constraints often create cognitive dissonance between individuals’ desire to travel and their ability to do so, leading to negative attitudes toward travel activities. Prior studies demonstrate that constraints can adversely affect attitudes, as seen in Huang and Hsu’s (2009) research, which revealed that constraints negatively impacted attitudes toward revisiting destinations. External constraints, such as work obligations, have been shown to shape attitudes toward leisure and travel negatively (Gao et al., 2019; Y. S. Lin et al., 2014). Therefore, the following hypothesis is proposed:

H1. 

Work-related travel constraints have a negative impact on attitudes toward travel.

Work-related travel constraints frequently limit access to critical resources like time and energy, diminishing individuals’ sense of control over their ability to travel. Empirical evidence indicates that external constraints, especially those stemming from professional demands, reduce confidence in overcoming obstacles and hinder travel intentions (M. F. Chen & Tung, 2014; Kuykendall et al., 2020). Thus, the following hypothesis is proposed:

H2. 

Work-related travel constraints have a negative impact on perceived behavioral control.

Subjective norms, which reflect social pressure or encouragement from significant others, can positively shape attitudes toward travel. For example, encouragement from family and peers can enhance the desirability of travel, even in the presence of constraints (Le et al., 2023). Research highlights subjective norms as a key determinant of attitudes in travel behavior. Therefore, the following hypothesis is suggested:

H3. 

Subjective norms about travel have a positive impact on attitudes toward travel.

Supportive subjective norms also bolster perceived behavioral control by fostering confidence in overcoming barriers. Social encouragement, such as emotional or logistical support, mitigates the effects of constraints and enhances the perceived ability to travel (Erul et al., 2023; Quintal et al., 2010). Thus, the following is hypothesized:

H4. 

Subjective norms about travel have a positive impact on perceived behavioral control.

Attitude, the extent to which a person views a behavior positively, is a vital factor influencing intention within the TPB framework (Soliman, 2021). Previous studies have consistently shown that favorable attitudes toward a certain behavior enhance the chances of developing an intention to engage in that behavior (Quintal et al., 2010; Seong & Hong, 2021). In the realm of travel, a positive attitude toward travel is often derived from feelings of enjoyment, relaxation, and personal growth linked to the experience. Such affirmative assessments are likely to boost individuals’ intent to travel, even when faced with limitations. Building on this insight within the larger travel context, H5 is proposed as follows:

H5. 

Attitude toward travel has a positive impact on travel intention.

In the TPB framework, subjective norms are influenced by the expectations of important individuals, such as family, friends, and peers (Ajzen & Fishbein, 1980). Numerous investigations have confirmed the significance of subjective norms in shaping behavioral intentions across different situations, including travel. For instance, Lee and Jan (2020) recognized subjective norms as a crucial predictor of travel intention among eco-tourists. When individuals believe that key referents endorse their travel decisions, they are more inclined to establish strong travel intentions, even when facing external limitations. This hypothesis is particularly pertinent in restricted travel situations, where support from social networks can help alleviate perceived obstacles and enhance travel intention. Therefore, H6 is hypothesized as follows:

H6. 

Subjective norms about travel have a positive impact on travel intention.

Perceived behavioral control (PBC) denotes individuals’ belief in their capacity to carry out a behavior, based on the resources and opportunities available (Ajzen, 2002). In the TPB model, PBC serves not only as a direct predictor of behavioral intention but also as a potential moderator of the connection between intention and actual behavior. In the context of travel, PBC includes aspects such as financial resources, availability of time, and understanding of travel logistics. Studies have indicated that higher levels of PBC boost individuals’ confidence in their ability to travel, thus elevating travel intention (Nguyen et al., 2023). For example, Meng and Cui (2020) found that PBC was the most influential factor affecting revisit intention behavior. Therefore, in the situation of limited travel, perceived control over the ability to navigate challenges is likely to positively influence travel intention, leading to H7 being proposed as follows:

H7. 

Perceived behavioral control about travel has a positive impact on travel intention.

Generally, constraints have been recognized to diminish individuals’ intent to travel. For instance, S. H. Park et al. (2017) found that travel restrictions such as language barriers, potential radiation risks, and anti-Japanese sentiments were significant constraints influencing Chinese college students’ travel intentions. Work-related travel constraints can also directly impede travel intention by creating notable psychological and practical barriers. When individuals encounter high levels of work-related constraints, their capability and desire to establish travel intentions are weakened. Previous studies have consistently shown that work-related factors adversely affect travel decision-making processes (Huang & Kim, 2021; Zhang et al., 2022). Consequently, the following hypothesis is proposed:

H8. 

Work-related travel constraints have a negative impact on travel intention.

Attitudes toward travel act as a crucial mediator in the connection between work-related travel constraints and travel intentions. Constraints adversely impact attitudes, which in turn lead to a reduction in travel intention. Empirical research in tourism has demonstrated that attitudes frequently mediate the negative impacts of external constraints on behavioral intention (Hüsser et al., 2023; Wang et al., 2022). Thus, we propose the following hypothesis:

H9. 

Attitude mediates the influence of work-related travel constraints on travel intention.

Subjective norms indirectly affect travel intention through attitudes, as supportive social pressure fosters positive attitudes toward travel. These enhanced attitudes subsequently elevate travel intention, even in constrained circumstances. Recent research in tourism literature highlights the mediating role of attitudes in the link between subjective norms and travel intentions (Lee & Jan, 2020; Wut et al., 2023). Hence, the following is hypothesized:

H10. 

Attitude mediates the influence of subjective norm on travel intention.

The conceptual model and main hypotheses are depicted in Figure 2.

4. Methodology

4.1. Data Collection and Questionnaire Design

Data for this research was collected in October 2024 through an online research firm in South Korea. The target population consisted of currently employed individuals, ensuring relevance to the study’s focus on work-related travel constraints. To achieve this, screening questions were implemented at the beginning of the survey to confirm respondents’ employment status.

The questionnaire was developed using validated measurement scales from previous research but was refined to ensure contextual relevance to work-related travel constraints. By implementing a structured refinement process and context-specific modifications, this study moves beyond the direct adoption of existing scales, making the questionnaire more tailored to the professional constraints that influence travel decision-making.

The construct of work-related travel constraints was measured using five items adapted from Tan and Chen (2021) and Y. S. Lin et al. (2014), with modifications to reflect professional obligations such as time scarcity, workload, and workplace norms regarding vacation-taking. The TPB variables—attitude, subjective norm, and perceived behavioral control—were measured using established scales from Quintal et al. (2010) and Meng and Cui (2020), with wording adjustments to align with the workplace context and ensure accurate measurement of employees’ perceptions and responses to travel constraints. Attitude was assessed with three items, subjective norm with four items, and perceived behavioral control with three items. Travel intention was measured using three items adapted from S. H. Park et al. (2017).

Given that the questionnaire was administered in a different linguistic and cultural setting, a translation and back-translation process was conducted to maintain semantic equivalence and enhance measurement validity. All measurement items were rated on a five-point Likert scale ranging from “strongly disagree” (1) to “strongly agree” (5), ensuring consistency across constructs. Following data collection, a total of 280 responses were obtained. After applying data purification processes, including checks for incomplete responses and response patterns indicating inattentiveness, 274 valid responses were retained for the final analysis. These refinements ensured that while the questionnaire retained its theoretical foundation, it was effectively tailored to examine the psychological and structural mechanisms influencing travel decisions in constrained professional environments.

The sample size appropriateness for this research can be evaluated in line with the PLS-SEM approach applied in this study. Given that Partial Least Squares Structural Equation Modeling (PLS-SEM) is variance-based and optimized for predictive modeling, it remains statistically robust even with moderate sample sizes, unlike Covariance-Based SEM (CB-SEM), which requires large samples for model convergence. According to Hair et al. (2019), the 10-times rule suggests that the minimum sample size should be at least 10 times the largest number of indicators per construct, which in this study would require a minimum of 30–50 respondents. With a final sample size of 274, this study far exceeds the recommended threshold, ensuring reliability, replicability, and the validity of the PLS-SEM analysis.

4.2. Data Analysis

Partial Least Squares Structural Equation Modeling (PLS-SEM) was selected for this study due to its suitability for exploratory research, theory extension, and predictive modeling, particularly in examining complex behavioral relationships within the extended Theory of Planned Behavior (TPB) framework (Hair et al., 2019; do Valle & Assaker, 2016). Unlike Covariance-Based SEM (CB-SEM), which primarily focuses on theory confirmation and model fit, PLS-SEM is variance-based, making it more appropriate for theory development and assessing newly integrated constructs, such as work-related constraints, within TPB. Given that this study represents one of the initial attempts to incorporate work-related constraints as direct antecedents to TPB constructs, PLS-SEM provides the flexibility needed to explore these relationships without the strict assumptions required in CB-SEM. Additionally, PLS-SEM is well-suited for models with moderate sample sizes and non-normal data, making it a robust choice given the study’s sample characteristics. Its ability to simultaneously estimate direct, indirect, and mediating effects ensures a comprehensive assessment of how work-related constraints influence attitudes, subjective norms, perceived behavioral control, and ultimately, travel intentions while maintaining methodological rigor.

To ensure a structured modeling process, the analysis followed a two-step approach. First, the measurement model was assessed to evaluate construct validity and reliability. Cronbach’s alpha and Composite Reliability (CR) were used to assess internal consistency, while convergent validity was examined through Average Variance Extracted (AVE). Discriminant validity was confirmed using the Fornell–Larcker criterion and Heterotrait–Monotrait (HTMT) ratio analysis, ensuring that each construct was distinct and measured appropriately.

After confirming the reliability and validity of the measurement model, the structural model was evaluated to test the hypothesized relationships. Path coefficients were estimated using bootstrapping with 5000 resamples, providing confidence intervals for statistical significance. Additionally, Variance Inflation Factor (VIF) diagnostics were conducted to detect and control for multicollinearity among predictor variables, ensuring that the results were not biased by collinearity issues.

By implementing this structured PLS-SEM modeling process, this study ensures a comprehensive and rigorous analysis of how work-related constraints influence travel intentions. The methodology captures both direct and indirect effects, providing valuable insights into the psychological and structural influences on constrained travel behavior.

To address common method bias (CMB), a combination of procedural and statistical remedies was applied. Procedurally, the survey was designed to minimize respondent biases by ensuring anonymity, randomizing item order, and using varied scale anchors to reduce pattern-based responses. Statistically, Harman’s single-factor test was conducted, and the results of an exploratory factor analysis showed that a single unrotated factor accounted for 28.0% of the variance, well below the 50% threshold, indicating that no single factor dominated the variance, thereby minimizing CMB concerns. Additionally, a full collinearity assessment approach was employed within the PLS-SEM framework, assessing variance inflation factors (VIFs) for all latent constructs. The results confirmed that all VIF values remained below the critical threshold of 3.3, ranging from 1.487 to 3.238, suggesting that common method variance does not significantly affect the study’s findings. These measures enhance the reliability of the measurement model and strengthen the robustness of the research conclusions.

5. Results

5.1. Demographic Profile

The sample of respondents consists primarily of males, who make up 58.8% of the group, while females account for 41.2%. Most participants are between the ages of 30 and 39 years (43.1%), followed by those aged 40–49 years (28.1%), 20–29 years (20.1%), and smaller proportions aged 50–59 years (7.7%) and 60 years or above (1.1%). In terms of marital status, half of the respondents are single (50.0%), with 47.8% married and 2.2% categorized as other. Regarding educational background, the majority hold a bachelor’s degree (62.8%), while 16.1% have a diploma or certificate, 13.1% have a high school education or less, and 8.0% possess a master’s degree or above. Monthly income levels vary, with the largest segment earning between USD 5000–USD 5999 (23.0%), followed by those earning under USD 2000 (21.2%) and in other income brackets (USD 3000–USD 3999) (19.0%). Occupation-wise, 30.1% of respondents are company employees, 19.1% are service workers, 16.1% are professionals, 13.4% are teachers or educators, and smaller percentages include researchers, engineers, self-employed individuals, and others. Most respondents took their last vacation within the past six months (52.2%), with others reporting vacations within one year (23.0%), two years (9.5%), or two or more years (6.2%), and a small group within the last month (9.1%). The demographic profile is outlined in

Table 1. Demographic profiles of respondents.

Characteristics	Frequency	%
Gender
Male	161	58.8
Female	113	41.2
Age
20s	55	20.1
30s	118	43.1
40s	77	28.1
50s	21	7.7
60s and above	3	1.1
Marital Status
Single	137	50.0
Married	131	47.8
Others	6	2.2
Education
High school graduate or less	36	13.1
Diploma/certificate	44	16.1
Bachelor’s degree	172	62.8
Master’s degree or above	12	8
Income (USD)
Under USD 2999	58	21.2
USD 3000–USD 3999	52	19.0
USD 4000–USD 4999	35	12.8
USD 5000–USD 5999	63	23.0
USD 6000–USD 6999	20	7.3
USD 7000 or above	46	16.8
Occupation
Professionals	44	16.1
Teacher/Educator	37	13.4
Company employee	83	30.1
Service workers	52	19.1
Researcher	30	11.0
Engineer	17	6.3
Self-employed	9	3.3
Others	2	0.6
Last Vacation
Within a month	25	9.1
Within 6 months	143	52.2
Within 1 year	63	23.0
Within 2 years	26	9.5
Within 2 or more years	17	6.2

.

5.2. Measurement Model

A two-stage analytical approach for PLS-SEM was adopted in which the measurement model was tested first, followed by an examination of the structural model (Hair et al., 2019). Findings regarding the validity and reliability of the scale are outlined in

Table 2. Validity and reliability of the scale.

Constructs	Items	Loadings	CR	Rho_a	AVE	Cronbach’s Alpha
Attitude	ATT1	2.988	0.924	0.920	0.803	0.879
	ATT2	2.838
	ATT3	2.007
Perceived Behavioral Control	PBC1	1.551	0.858	0.814	0.669	0.760
	PBC2	1.487
	PBC3	1.578
Social norm	SN1	3.314	0.940	0.948	0.797	0.917
	SN2	2.790
	SN3	2.758
	SN4	3.784
Travel intention	TI1	4.662	0.969	0.953	0.913	0.953
	TI2	5.810
	TI3	5.586
Work constraint	WTC1	3.057	0.936	0.918	0.746	0.915
	WTC2	3.876
	WTC3	3.238
	WTC4	2.652
	WTC5	2.436

. In examining construct reliability and validity of the measurement model, reliability was determined using Cronbach’s Alpha and Composite Reliability (CR). Both metrics exceeded 0.8 for all factors ranging from 0.858 to 0.969, indicating high internal consistency. Convergent validity was assessed through Average Variance Extracted (AVE) and factor loadings, with AVE values surpassing the accepted threshold of 0.5, ranging from 0.746 to 0.913, and all item loadings above 0.7. These results confirmed the convergent validity of the model (Hair et al., 2019).

To assess discriminant validity, we employed the Fornell–Larcker criterion (Fornell & Larcker, 1981). The square root of the AVE for each factor exceeded its corresponding correlation coefficients, indicating discriminant validity. However, recent critiques suggest that the Fornell–Larcker criterion may not reliably detect a lack of discriminant validity in typical research scenarios Henseler et al. (2015). Therefore, we also tested discriminant validity using the Heterotrait–Monotrait ratio of correlation (HTMT). The recommended HTMT value should be below 0.85 or 0.9 (Franke & Sarstedt, 2019; Rasoolimanesh, 2022). Results showed that all HTMT values were below 0.85, the highest being 0.740 (

Table 3. HTMT (Heterorait–Monotrait) analysis.

	1	2	3	4	5
Attitude
Perceived Behavioral Control	0.449
Social norm	0.622	0.562
Travel intention	0.670	0.462	0.566
Work constraint	0.401	0.740	0.380	0.553

). These findings confirmed an acceptable level of discriminant validity for the model.

5.3. Structural Model

Before analyzing the structural model, collinearity was assessed using the Variance Inflation Factor (VIF) as recommended. All VIF values were below the conservative threshold of 3.3, ranging from 1.487 to 3.238. Such a finding indicates no collinearity issues within the structural model (Hair et al., 2019).

Furthermore, the coefficient of determination ($R^2$) and predictive relevance $Q^2$ were utilized to evaluate the proposed structural model. The findings revealed that $R^2$ values of latent variables were all above the threshold of 0.20 as indicated in Figure 2. The $Q^2$ values were all larger than 0 for all endogenous constructs, ranging from 0.04 to 0.461, indicating the predictive power of the proposed structural model.

In order to test hypotheses, the proposed structural model was evaluated using 5,000 bootstrap resamples (see

Table 4. Results of hypotheses testing.

Hypotheses		Beta	t-Value	p-Value	Supported
H1	WTC→ATT	−0.199	4.231	0.000	Yes
H2	WTC→PBC	−0.547	12.813	0.000	Yes
H3	SN→ATT	0.500	8.095	0.000	Yes
H4	SN→PBC	0.280	4.982	0.000	Yes
H5	ATT→TI	0.401	6.860	0.000	Yes
H6	SN→TI	0.227	3.717	0.000	Yes
H7	PBC→TI	−0.046	0.716	0.474	No
H8	WTC→TI	−0.304	5.163	0.000	Yes
H9	WTC→ATT→TI	−0.080	4.226	0.000	Yes
H10	SN→ATT→TI	0.200	4.678	0.000	Yes

and Figure 3). The results revealed that work-related travel constraints have significant negative effects on attitude ($\mathsf{\beta }$ = −0.199, p < 0.001) and perceived behavioral control ($\mathsf{\beta }$ = −0.547, p < 0.001), supporting hypotheses 1 and 2. Moreover, it was found that subjective norms about travel have a significant positive impact on attitude toward travel ($\mathsf{\beta }$ = 0.500, p < 0.001) and perceived behavioral control ($\mathsf{\beta }$ = 0.280, p < 0.001). Thus, hypotheses 3 and 4 were supported. Attitude toward travel ($\mathsf{\beta }$ = 0.401, p < 0.001) and subjective norms about travel ($\mathsf{\beta }$ = 0.227, p < 0.001) were found to have significant and positive impacts on travel intentions. Therefore, hypotheses 5 and 6 were supported. However, the effect of perceived behavioral control about travel on travel intention was not significant, and H7 was rejected. Work-related travel constraints were found to have a significant negative impact on travel intention, supporting H8 ($\mathsf{\beta }$ = −0.304, p < 0.001). In addition, the results showed that all hypothesized indirect effects were significant, where attitude mediates the impact work constraint has on travel intention ($\mathsf{\beta }$ = −0.080, p < 0.001) as well as the influence of social norms on travel intention ($\mathsf{\beta }$ = 0.200, p < 0.001).

6. Conclusions and Discussion

6.1. Conclusions

This study investigates the intricate relationship between work-related travel constraints and various psychological factors that influence travel intentions, framed within the context of the extended Theory of Planned Behavior (TPB) (Ajzen, 2002). By incorporating work-related constraints into an extended TPB framework, this research provides a deeper understanding of how professional obligations shape attitudes, perceived behavioral control, and subjective norms regarding travel. While the negative impact of work constraints on travel intentions is well acknowledged, empirical validation within a structured theoretical model is crucial for advancing theoretical understanding and informing practical interventions. The findings reinforce the significance of contextualizing external constraints in travel behavior research, particularly for employees whose professional commitments limit their ability to engage in leisure travel. By extending TPB to explicitly integrate work constraints as psychological determinants rather than external inhibitors, this research offers a more nuanced understanding of how modern work structures impact travel decision-making.

This study revealed that work-related constraints significantly and negatively influence attitudes and perceived behavioral control, ultimately shaping travel intentions. This empirical validation of a known phenomenon highlights how work demands erode enthusiasm for travel and diminish confidence in one’s ability to navigate travel challenges, underscoring the need for organizational interventions to mitigate these barriers. Consistent with prior research (Gao et al., 2019; Kuykendall et al., 2020), these findings quantify the impact of workplace obligations on individuals’ psychological engagement with travel opportunities.

Moreover, the results showed that subjective norms have a positive and significant impact on both attitudes and perceived behavioral control regarding leisure travel. This underscores the critical role that social factors play in shaping individuals’ perceptions and feelings towards travel. When individuals are surrounded by supportive social networks at work, they are more likely to foster positive attitudes towards travel experiences and develop a robust sense of confidence in their ability to navigate and overcome potential obstacles. This aligns with the conclusions drawn from earlier research conducted by Liu and Park (2024) and Quintal et al. (2010), which similarly emphasized the importance of social influences in empowering individuals to pursue their travel aspirations with greater assurance.

This study also partially supported the traditional TPB framework, with attitude and subjective norms identified as significant predictors of travel intention. The findings of this research validated the positive impact of personal attitudes and perceived social norms concerning leisure travel on individuals’ travel intentions for employees, underscoring the essential role of both personal beliefs and societal influences in shaping one’s inclination to travel for leisure. These findings expand the discussion from other contexts that employed the Theory of Planned Behavior (Lee & Jan, 2020; Seong & Hong, 2021) to encompass work-related travel constraints, indicating that employees’ beliefs and social norms can greatly affect their willingness to travel.

However, the effect of perceived behavioral control (PBC) on travel intention was found to be insignificant, diverging from much of the TPB literature, where PBC is typically a strong predictor. This finding underscores the context-dependent nature of perceived control, particularly in constrained environments where external limitations override individual agency. In traditional leisure contexts, PBC influences travel intention by increasing individuals’ confidence in their ability to travel. However, in work-constrained environments, even individuals with high perceived control may still be unable to act on their intentions due to rigid work schedules, professional responsibilities, and organizational expectations. This aligns with Ajzen’s (2002) assertion that PBC’s effect is contingent on situational factors, suggesting that in highly constrained settings, external barriers weaken the influence of perceived control on decision-making. Similar findings have been observed in studies where external pressures, such as financial constraints or legal restrictions, override personal control in behavioral intentions (S. H. Park et al., 2017). Thus, the insignificant effect of PBC in this study suggests that work-related constraints impose structural limitations that reduce individuals’ ability to translate control perceptions into travel intentions, reinforcing the necessity of examining such constraints within behavioral decision-making models.

Work-related travel constraints were also found to exert a significant negative impact on travel intentions, reinforcing the notion that such constraints act as major barriers to forming travel plans. This finding aligns with prior studies (S. H. Park et al., 2017; Huang & Kim, 2021; Zhang et al., 2022) and underscores the need for targeted strategies to reduce the impact of professional obligations on leisure travel, such as workplace policies promoting vacation time and flexibility in scheduling.

Finally, the mediating role of attitude was confirmed in two key pathways: between work-related constraints and travel intention, and between subjective norms and travel intention. These results highlight the central importance of attitudes in shaping travel intentions, even in constrained contexts. Attitude serves as a crucial mechanism through which external influences, like social support or constraints, translate into behavioral intentions. Consistent with prior research (Hüsser et al., 2023; Lee & Jan, 2020), these findings suggest that fostering positive attitudes through targeted interventions, such as workplace support for leisure and social encouragement, could mitigate the adverse effects of constraints and promote travel behaviors more effectively.

6.2. Theoretical Implications

This study represents one of the early endeavors to comprehend the influence of work-related constraints on travel intentions and the psychological mechanisms underlying this relationship. While much of the extant literature on the intersection of work and leisure travel focuses on the positive outcomes of leisure trips, such as alleviating work-related stress or enhancing productivity (Tripathi, 2021), there has been a significant oversight in addressing the reverse dynamic: how work-related constraints hinder individuals from pursuing leisure travel. By shifting the perspective, this study broadens the understanding of the interplay between work and leisure. Instead of solely emphasizing the benefits of leisure travel on work-related outcomes, it investigates how work-related constraints shape the travel decision-making process.

Exploring the role of work-related constraints on travel intention is also important in the sense that this research underscores the active role of constraints in the travel decision-making process. While the negative effect of work constraints on travel may appear intuitive, empirical validation within a structured decision-making framework is essential for advancing both theoretical understanding and practical interventions. Existing research often treats constraints as passive barriers without examining their role in shaping perceptions and attitudes within a behavioral model (C. C. Chen & Petrick, 2016; M. F. Chen & Tung, 2014). By demonstrating that work-related constraints actively influence attitudes and perceived behavioral control, this study challenges simplistic classifications of constraints as external obstacles and underscores their role as psychological determinants within TPB.

Additionally, this research builds upon prior studies that primarily address the disruptive effects of work-related demands during vacations (S. Park & Lehto, 2024) by extending the discussion to the pre-trip phase. It highlights how these constraints function as barriers to leisure travel long before the journey begins. In doing so, this study offers a more comprehensive framework for understanding the work–leisure nexus. By addressing the underexplored role of work-related constraints in travel intention, it enriches the existing literature on the interplay between work and leisure during and post-travel. It also highlights the necessity of considering how work-related factors deter individuals from engaging in leisure trips, emphasizing the importance of acknowledging not only the restorative benefits of leisure vacations but also the barriers that prevent individuals from accessing these benefits.

Furthermore, this study critically engages with past research that has incorporated work-related constraints within broader leisure behavior models, such as the work–leisure conflict (WLC) framework. While previous studies have examined the impact of work obligations on leisure participation (Tsaur et al., 2012; Y. S. Lin et al., 2014), these models primarily conceptualize work constraints as generalized lifestyle conflicts rather than examining their direct role in shaping travel decision-making. Prior WLC models focus on the spillover effects of work demands on leisure satisfaction and well-being (Y. S. Lin et al., 2014; J. H. Lin et al., 2015), but they often do not position work-related constraints as integral determinants within a structured behavioral model. By integrating work-related constraints directly into the Theory of Planned Behavior (TPB), this study advances the theoretical discussion by demonstrating how these constraints influence attitudes, subjective norms, and perceived behavioral control (PBC), ultimately shaping travel intentions. This distinction moves beyond previous research that primarily examines the consequences of work–leisure conflict and instead explores the mechanisms through which these constraints influence travel choices.

This research makes a notable contribution to the travel constraints literature by addressing a critical gap in the study of context-specific constraints. While much of the prior research has focused on generic leisure constraints theory (Kazeminia et al., 2015; Tao et al., 2019; Karl et al., 2020), this framework has often been applied to travel contexts without sufficient adaptation. Consequently, work-related travel constraints—a distinct and highly relevant category—have remained underexplored. By targeting work-related constraints specifically, this study moves beyond generalized travel constraints and investigates how professional obligations uniquely shape travel behavior. Even in studies examining specific populations, such as seniors or pet owners, researchers have primarily relied on leisure constraints theory, which limits contextual applicability. In contrast, this research directly examines the nuances of work-related travel constraints, offering a more precise understanding of their impact on decision-making processes. This targeted approach enhances the theoretical relevance of the findings and establishes a foundation for future research to explore other context-dependent constraints with similar rigor.

In addition, this research advances the conceptualization of travel constraints by advocating for a redefinition of their dimensional structure within leisure constraints theory. The traditional categorization of constraints into intrapersonal, interpersonal, and structural dimensions (Crawford et al., 1991) has proven useful but often amalgamates diverse factors under broad classifications, potentially obscuring the unique and multifaceted nature of specific barriers. For example, work-related constraints have traditionally been subsumed under the structural dimension as external factors discouraging participation. However, this study demonstrates that work-related constraints are sufficiently distinct and influential to function as a standalone construct. By isolating these constraints, this research highlights the limitations of the existing framework and underscores the need for greater contextual specificity when analyzing travel constraints. This refined perspective not only deepens our understanding of how structural barriers operate but also encourages further investigation to diversify and reexamine the dimensions of travel constraints to reflect the complexity of real-world contexts.

Lastly, this research contributes to advancing the understanding of the Theory of Planned Behavior (TPB) by integrating work-related travel constraints as a predictor within the traditional TPB framework. By validating the extended model, this study underscores its robustness in examining the interplay between work-related constraints and travel behavior, offering deeper insights into how contextual barriers shape decision-making processes. The findings highlight the importance of integrating context-specific constraints, such as professional obligations, into behavioral models, thereby illuminating the dynamic relationship between external barriers and the psychological constructs central to TPB—attitudes, subjective norms, and perceived behavioral control. This nuanced approach underscores that travel decisions are not made in isolation but are instead embedded within a complex web of contextual and psychological influences along with work-related travel constraints.

6.3. Practical Implications

The findings of this study provide actionable insights for organizations, policymakers, and tourism practitioners in addressing work-related travel constraints and fostering a work environment that facilitates leisure travel. Given the significant negative impact of work-related constraints on travel intentions, workplace policies should go beyond mere availability of vacation time and actively create conditions that reduce perceived psychological and structural barriers. Employers should recognize the strategic benefits of encouraging travel, such as improved employee well-being, engagement, and productivity, and implement structured policies that promote flexible scheduling, mandated vacation use, and transparent leave policies to mitigate time-related constraints.

Moreover, this study highlights the critical role of subjective norms in shaping employees’ attitudes toward travel. Organizational culture must shift beyond policy implementation to actively promote travel as a socially accepted and encouraged behavior. Many employees hesitate to take vacations due to workplace stigmas or concerns about professional consequences. Employers can counteract this by integrating travel encouragement into corporate wellness programs, offering incentives for leave utilization, and ensuring senior leaders model vacation-taking behaviors to normalize time off. Awareness campaigns that emphasize the work–life balance benefits of leisure travel and highlight peer endorsements and leadership support can further help create a more travel-supportive work environment.

For the tourism sector, these findings suggest a need for more adaptive and flexible travel solutions for employees with constrained schedules. Travel providers should develop short-duration travel packages, flexible cancelation policies, and customized itinerary planning that accommodate professionals with limited availability. Additionally, the integration of “bleisure” travel—combining business and leisure—can provide an alternative avenue for employees to incorporate travel within their work commitments. Marketing strategies should address work-related travel concerns by emphasizing minimal disruptions to professional obligations while highlighting the psychological and physical benefits of travel.

Technology can also play a vital role in supporting constrained travelers by offering digital tools that facilitate real-time itinerary adjustments, seamless scheduling, and work–travel integration. Mobile apps that provide personalized travel recommendations based on work constraints, automated schedule synchronization, and real-time flexibility options can enable professionals to travel without significant disruptions to their responsibilities.

From a policy standpoint, regulatory frameworks should reinforce the right to take leave without negative professional consequences. Governments and organizations could introduce mandatory vacation policies, enforceable work–life balance regulations, or incentives for companies that actively promote employee well-being through leisure travel. These interventions can help ensure that employees are not only provided with the opportunity to take vacations but are also encouraged to do so without career penalties.

By addressing both structural and psychological barriers, employers, policymakers, and tourism providers can contribute to a system where employees feel empowered to take vacations without professional repercussions, ultimately fostering greater well-being, work satisfaction, and a more sustainable work–life balance while supporting the travel industry.

6.4. Limitations

Despite its contributions, this study has several limitations that should be acknowledged. First, this study was conducted within a single cultural and geographical context, which may limit the generalizability of the findings to other regions or countries. Work-related travel constraints are influenced by national labor policies, workplace cultures, and societal attitudes toward vacation-taking, all of which can vary across different economic and cultural environments. Future studies should consider cross-cultural comparisons or multi-country analyses to examine whether the relationship between work-related constraints and travel behavior remains consistent across different labor markets and cultural settings.

Moreover, the measurement of work-related constraints was designed from a macro-level perspective, drawing on validated scales to provide a generalized assessment applicable across diverse employment contexts. While this approach ensures comparability with prior research, it may not fully capture specific workplace constraints. Future studies should consider qualitative methods, such as employee interviews or focus groups, to refine the construct and develop more context-specific measurements that better reflect the diverse ways work-related constraints impact travel behavior.

Another limitation of this study is that the sample was not systematically stratified by the work sector, meaning that while diverse occupations are represented, industry-specific variations in work-related travel constraints were not explicitly analyzed. Different professional environments may impose varying levels of travel restrictions, and sector-specific policies could influence how employees perceive and navigate these constraints. Future research should consider sector-focused sampling strategies or comparative studies across industries and cultures to examine whether workplace constraints on travel differ systematically between occupational fields.

Finally, the reliance on self-reported data introduces the possibility of social desirability bias, where respondents may provide overly favorable or unfavorable accounts of their attitudes and behaviors. Employing objective measures, such as travel records or employer data on leave usage, could help validate the findings and reduce potential biases. Addressing these limitations will enhance the robustness of future research and contribute to a deeper understanding of the factors influencing constrained travel behavior.