Abstract
This study, guided by the broaden-and-build theory (BBT), examines the relationship between leisure travel frequency and tourists’ quality of life (QoL), with happiness and psychological resilience as key mediators. We also explore how tourists’ coping abilities and perceived vulnerability levels shape this relationship as moderators. Using cross-sectional surveys with Australian tourists at three time points (Study 1–n = 599, Study 2–n = 290, Study 3- n = 379), we evidence the connection between travel frequency and QoL, highlighting the mediating roles of happiness and psychological resilience. Individuals with weaker coping abilities and high vulnerability levels are also shown to benefit more from increased travel frequency in terms of QoL. These findings deepen our understanding of the link between leisure travel and QoL, identifying the types of tourists who gain the most from frequent travel. Theoretical and managerial implications are discussed in line with these findings.
Introduction
Over the past three decades, the impact of travel on quality of life (QoL) has been extensively studied in tourism (Chen & Petrick, 2013; Uysal et al., 2016). The prevailing opinion is that travel has the capacity to increase one’s QoL, particularly that of tourists, by enhancing their life satisfaction (Chen et al., 2016). However, significant knowledge gaps persist regarding the antecedents of tourists’ QoL, potential mediators, and moderators that explain how and why travel may be associated with QoL (Berbekova et al., 2022; Su et al., 2023). This research aims to address three of these gaps in the tourism literature.
Firstly, limited studies consider leisure travel frequency as a positive determinant of QoL (Su et al., 2023). Travel in general, and by implication travel frequency, can potentially provide different and enriching experiences that broaden individuals’ mindsets through positive emotions (Cao et al., 2020) and improved wellbeing, suggesting that increased leisure travel could enhance QoL (Mitas & Kroesen, 2020; Zheng et al., 2022). Secondly, there is a lack of understanding around the psychological mechanisms underpinning why higher QoL would be linked to more leisure travel. Existing studies tend to focus solely on direct effects, neglecting potential mediators that elucidate the underlying psychological processes transforming more travel into QoL improvements (Mitas & Kroesen, 2020; Su & Swanson, 2020; Zheng et al., 2022). Thirdly, there has been limited exploration into how individual differences in tourists’ psychological abilities, including cognitive functions, could influence the relationship between leisure travel frequency and QoL. Viewing travel as a strategy to broaden and build from positive emotions and enhance personal resources, it becomes imperative to comprehend moderating factors such as coping mechanisms and vulnerability to grasp how different tourists may derive varying levels of benefit from travel. For example, tourists with strong coping abilities (low perceived vulnerability) may not experience significant increases in QoL with higher leisure travel frequency, as they might already be at a high threshold of positive emotions and personal resources which cannot be significantly enhanced. Conversely, individuals with lower coping abilities (high perceived vulnerability) might experience the opposite effect, with greater increases in QoL from increased leisure travel. Understanding these nuances can provide valuable insights into the complex interplay between travel, individual differences, and QoL. Yet, whether this is in fact the case requires empirical validation. Despite evidence of a positive association between travel and QoL, the underlying mechanisms and explanatory factors remain largely unexplored (Uysal et al., 2020 ; Zheng et al., 2022). Therefore, this study aims to address these three knowledge gaps regarding the association between tourist leisure travel frequency and QoL.
A theoretical framework addressing these gaps is provided by the broaden-and-build theory (BBT), a positive psychology theory focusing on human strengths and optimal functioning rather than psychological disorders or deficits (Fredrickson, 2001; Vada et al., 2020). BBT specifically emphasizes how positive emotions can cultivate enduring personal resources, thereby promoting adaptive functions and greater well-being (Fredrickson, 2001). Thus, the current research examines how the association between leisure travel and QoL can be understood through the positive emotion of happiness and the personal resource of psychological resilience. Despite the recognized importance of positive emotions (Hosany & Gilbert, 2010; Prayag et al., 2017) and resilience (Prayag, 2023) in tourism studies, their combined role as explanatory mediators for travel outcomes such as QoL remains underexplored. This also includes existing studies guided by BBT that focus on QoL indicators (Mitas & Kroesen, 2020; Su & Swanson, 2020; Zheng et al., 2022). Thus, while there is evidence suggesting that the underlying principles of BBT can explain the link between travel frequency and QoL, there is no comprehensive evaluation of how experiences of happiness and increases in the personal resource of psychological resilience may elucidate this link. Consequently, the first research question is: Can happiness and psychological resilience serve as serial mediators for the relationship between higher leisure travel and QoL?
The second research question is: Do pre-existing psychological resources (coping ability and perceived vulnerability) of tourists affect the association between leisure travel frequency and QoL? Previous tourism research has delved into QoL disparities tied to demographics, geography, and destinations (H. Kim et al., 2015; Su et al., 2023; Zheng et al., 2022) but not psychological resources. Individuals’ pre-existing psychological resources may shape the link between leisure travel frequency and tourist QoL because: (i) tourists’ coping ability aids in stress management and fosters positive emotions during travel (C. Cheng et al., 2014; Jordan & Prayag, 2022) and (ii) through travel experience, tourists become more confident in dealing with unforeseen circumstances (Gottschalk et al., 2022), which reduces feelings of vulnerability, reflecting decreased perceived susceptibility to harm (Mulcahy et al., 2023; Riedel et al., 2021). Coping acts as a shield against stressful tourism experiences (Hossain et al., 2023; Jordan & Prayag, 2022). Another pre-existing psychological factor is tourists’ perceived vulnerability with existing research mainly focusing on vulnerability among other tourism stakeholders (Espiner & Becken, 2014). The consideration of tourist vulnerability and its impact on travel experiences and QoL benefits remains inadequately explored (Boakye, 2012). Understanding how tourists’ vulnerability moderates the relationship between travel frequency and QoL can shed light on conditions that enhance or diminish benefits for different tourist groups.
To address the two research questions, this study analyzes cross-sectional data collected at three time points (Study 1: n = 599, Study 2: n = 290, Study 3: n = 379), with hypotheses grounded in BBT. This method not only emphasizes the generalizability of relationships across various time points and samples but also explores the stability of these connections during crises like the COVID-19 pandemic, meeting recent calls for such research (Assaf et al., 2022). In addressing the research questions, this study significantly contributes to tourism scholarship and the application of positive psychology frameworks.
Firstly, by utilizing BBT, the study demonstrates how happiness and psychological resilience function as serial mediators for the link between increased leisure travel frequency and QoL, a relationship not yet fully explored in current literature. In addition, the current study provides evidence that leisure travel, and potentially other related aspects such as vacation duration, can have lasting positive effects beyond the short-term. The research indicates that stable states like happiness, resilience, and QoL can be enhanced through increased leisure travel, with effects that endure over time rather than being short-lived. This contributes to the ongoing discussion on the benefits of tourism for QoL and wellbeing (Smith & Diekmann, 2017; Zins & Ponocny, 2022), suggesting that travel impacts these aspects not only in the short-term but also in the long-term, particularly when undertaking more frequently by tourists, thereby contributing to sustaining and enhancing happiness and QoL. Secondly, the research highlights coping ability and vulnerability as crucial moderating factors, shedding light on who benefits most from increased leisure travel in terms of enhanced QoL. This shift moves considerations away from demographic factors toward individual psychological differences, which may explain variations in the strength of these relationships among different tourists.
From a practical standpoint, this research offers implications for tourism marketing, policy makers, and mental health professionals. The findings also underscore how policy makers can advocate for investments in infrastructure and policies that encourage more frequent and responsible travel, thereby enhancing individual QoL. Additionally, the research supports marketing efforts that highlight the benefits of frequent travel for improving QoL and happiness. These insights provide a foundation for collaborative efforts among stakeholders to promote responsible travel to foster well-being and satisfaction among the population. Furthermore, as more vulnerable individuals are shown to have greater levels of QoL improvements associated with more frequent leisure travel, designing experiences or promoting toward this market should be considered. The subsequent section of the paper presents the theoretical background of the study, followed by its hypotheses.
Theories of Positive Psychology
Positive psychology explores the positive aspects of human behavior through psychological theory, research, and interventions (M. E. P. Seligman, 1998). It encompasses hedonic wellbeing (e.g., happiness and life satisfaction), eudemonic wellbeing (e.g., meaning, purpose, and engagement), flourishing, and QoL (Gallagher et al., 2009; M. E. Seligman & Csikszentmihalyi, 2000). To flourish, individuals need positive emotions, engagement, and meaning, along with resilience, optimism, self-esteem, and vitality (Huppert & So, 2009). In tourism studies, there is a focus on assessing conditions for wellbeing and highlighting the positive impacts of tourism on individuals and communities (Filep & Laing, 2019). While integrating these concepts is challenging, the current study emphasizes the hedonic facet of wellbeing, resilience, and factors influencing QoL. Specifically, the current research considers testing the theoretical underpinnings of BBT regarding how positive emotions enhance psychological resources that may help tourism scholarship gain an understanding of why leisure travel frequency may be associated with higher levels of QoL for tourists. Such a deduction from BBT is plausible considering that frequent leisure travelers have more varied experiences and potentially a greater range and depth of positive emotions, such as happiness, during their trips. This could result in increased psychological resources, such as heightened resilience, enabling them to effectively navigate challenging situations and ultimately enhance their QoL, promoting flourishing and wellbeing.
Efforts to enhance happiness often revolve around fostering positive emotions (Seligman et al., 2005). Positive emotions, as studied in BBT by Fredrickson (2001), contribute to personal flourishing. Unlike cognitive appraisal theory (Roseman, 2001) and the transactional model of stress (Lazarus & Folkman, 1984), which focus on negative emotions and stressors, positive psychology and BBT aim to cultivate positive emotions, strengths, and virtues (Fredrickson, 2001). BBT explores how positive emotions expand cognitive and behavioral capabilities, promoting flourishing (Fredrickson, 2001). It emphasizes the consequences of emotional reactions rather than their antecedents, complementing cognitive appraisal theories. By shifting away from deficit-based approaches to adversity, BBT offers a perspective focused on growth and flourishing, particularly in the context of travel outcomes.
BBT emphasizes how positive emotions enhance attention and cognition, fostering flexible thinking (Fredrickson, 2001), which is crucial for resilience. Positive emotions equip individuals with coping skills, expanding their ability to adapt (Fredrickson, 2001; Garland et al., 2010), similar to outcomes observed in stress models. Resilient individuals effectively regulate emotions, finding positive meaning in adversity (Tugade & Fredrickson, 2004), as positive emotions underpin psychological resilience and well-being (Tugade & Fredrickson, 2004). BBT elucidates how happiness and QoL intersect with resilience, and the role of coping strategies in shaping these relationships (Fredrickson, 2001; Waters et al., 2022). Positive psychology regards coping strategies as fundamental for resilience (Waters et al., 2022), recognizing their interaction with mental health outcomes (Lomas & Ivtzan, 2016). From this perspective, psychological distress can yield positive outcomes through buffering (coping), where positive emotions mitigate distress, bolstering resilience by maintaining mental health amid adversity, and a building effect occurs when adversity fosters new perspectives, enhancing meaning and improving mental health (Waters et al., 2022). Given this evidence and theoretical underpinnings, BBT could offer a deeper explanation that enhances understanding of how and why leisure travel frequency is associated with QoL, as well as why certain factors may explain its association (happiness and psychological resilience) while others may elucidate the strength or weakness of these relationships (coping ability and vulnerability).
QoL and Tourism Research
This research considers one indicator of QoL, life satisfaction, defined as how favorably tourists judge the overall quality of their life (D. Kim et al., 2024). Life satisfaction as a QoL indicator has been argued to be of key importance as a gauge of tourism performance (Berbekova et al., 2022; Uysal et al., 2016), particularly when considering its impact on tourists. Tourism scholars grapple with delineating happiness, wellbeing, and QoL, as often these terms are used interchangeably, as highlighted in the tourism literature on positive psychology (Filep & Laing, 2019; Vada et al., 2020). Aligning with Vada et al.’s (2020) recommendations, we therefore conceptualize happiness and QoL as distinct yet closely related constructs (Vada et al., 2020) and as detailed shortly, consider happiness as an antecedent which explains why QoL is associated with leisure travel.
Compared to subjective well-being, QoL assessments provide more comparable measures across populations and contexts, aiding robust analysis of travel frequency, and tourism experiences’ impact on overall QoL. By prioritizing QoL, our study aims to uncover factors influencing life satisfaction, informing policies and interventions to enhance well-being and recognize tourism’s transformative potential. Essential elements include subjective measures like satisfaction with different life domains, including emotional well-being derived from leisure activities (Kim et al., 2013).
As outlined in the literature review (Table 1), numerous studies have investigated travel and tourism experiences alongside outcomes closely linked to QoL (e.g., Mitas & Kroesen, 2020), while others have delved into happiness (Paramita, 2021), and psychological resilience (Mulcahy et al., 2023; Prayag 2023), all of which could be collectively examined guided by the principles of the BBT (Cohn et al., 2009). Despite the existing body of literature addressing these domains—leisure travel and QoL, happiness, psychological resilience, coping, and vulnerability—somewhat independently, there exists a gap in integrating these concepts to offer a more complete understanding of how and why travel frequency correlates with QoL. This research aims to bridge this gap by examining the mechanisms, such as happiness and psychological resilience, that elucidate this relationship and aligns with BBT, as well as identifying factors that may moderate its strength, such as coping ability and vulnerability. Subsequently, the hypothesized relationship between these concepts, based on theory and supported by empirical evidence from the literature, is presented.
Overview of Related Tourism and BBT Literature.
Leisure Travel Frequency and QoL
Tourism scholarship has considered the impacts of travel and tourism experiences on QoL from multiple perspectives, including those of tourists (e.g., Chen et al., 2016; Filep & Laing, 2019; Neal et al., 2007), residents (Su et al., 2023), and destination or community perspectives (e.g., Berbekova et al., 2022). As Filep and Laing (2019) note, studies devoted to the understanding of well-being from tourist perspectives abound, but these are not always integrative of other positive psychology concepts. Nonetheless, the significance of QoL as an indicator of destination success has been ascertained (Uysal & Sirgy, 2019), and its path as an outcome of satisfactory tourist experiences has been established (Berbekova et al., 2022). In the current research, a pathway to QoL is considered to be associated with a higher amount of leisure travel.
While a body of literature exists on QoL in tourism, few studies have comprehensively investigated the association of leisure travel frequency on tourists’ perceptions of QoL. Notably, research from both resident (Su et al., 2023) and tourist perspectives (Chen et al., 2016) has not extensively explored the emotional responses, such as happiness, and personal resources, including psychological resilience, coping ability, and vulnerability, that may elucidate the association between tourism experiences and QoL. Understanding how tourism experiences impact QoL, as well as the interplay between positive emotions and psychological resources, can enhance our understanding of QoL assessment and design indicators (Berbekova et al., 2022).
When considering studies utilizing BBT in tourism, emerging evidence supports the notion that leisure travel can enhance tourists’ QoL or related outcomes (Mitas & Kroesen, 2020; Su & Swanson, 2020; Zheng et al., 2022). For example, the work of Mitas and Kroesen (2020) shows that more frequent vacationers from the Netherlands experience higher life satisfaction and positive affect than those with lower frequencies. Su and Swanson (2020) demonstrate how levels of eudaimonia and hedonia (well-being) increase and decrease over time based on the type of tourism activity (relaxing vs. challenging). While not specifically underpinned or guided by BBT, like Su and Swanson (2020) and Mitas and Kroesen (2020), the results of Zheng et al. (2022) are consistent with these prior studies showing that an increase in tourism intensity, specifically, the number of nights individuals stayed away from home on vacation or visiting family and friends, was associated with a higher level of subjective well-being for Chinese individuals. In addition to Zheng et al. (2022), Chen and Yoon’s (2019) study of American tourists demonstrates that a higher number of leisure trips was associated with higher life satisfaction. These findings support the current research’s position that there should be a positive and significant association between higher leisure travel frequency and tourists’ QoL. In fact, as tourists travel more, they should be able to increase their cognitive repertoire and grow from the experiences, which aligns with the central tenets of BBT.
While these studies (Chen & Yoon, 2019; Mitas & Kroesen, 2020; Su & Swanson, 2020; Zheng et al., 2022) begin to establish a link between higher levels of leisure travel and QoL or other related indicators, their explanation as to the process which explains why this occurs requires further exploration. The current research suggests there are potentially two theoretical explanations from BBT to suggest why higher leisure travel frequency may be associated with higher levels of QoL in tourists. The first is related to positive emotions, whereby leisure travel may provide tourists the opportunity to travel to new destinations, immerse themselves in diverse cultures, and engage in novel activities, eliciting positive emotions such as happiness, which contribute to expanding one’s perspective and bolstering psychological resources, leading to the second theoretical justification.
The second potential explanation for the association between higher travel frequency and higher levels of QoL in tourists is due to enhanced personal resources, such as psychological resilience. Theoretically, the association between travel frequency and QoL, from BBT, may be due to these events exposing tourists to varied environments and navigating new challenges during travel, which can fortify psychological resilience. Coping with unforeseen circumstances, adapting to unfamiliar cultures, and overcoming obstacles encountered while traveling can cultivate resilience (Gottschalk et al., 2022). However, as indicated in the literature overview presented in Table 1, these potential explanations rooted in BBT have yet to be firmly established or empirically examined. Collectively, existing studies do not provide the explanatory mechanisms (mediators) that would enable a deeper understanding of the relationship between travel frequency and QoL.
Despite these gaps, there is evidence suggesting that an association likely exists between travel frequency and QoL as previously discussed (Mitas & Kroesen, 2020; Su & Swanson, 2020; Zheng et al., 2022). Therefore, aligned with this current literature and BBT, the present research posits the following hypothesis:
Tourist Experiences of Happiness and Psychological Resilience
As previously mentioned in H1, BBT posits two reasons for the association between travel frequency and QoL: heightened experiences of positive emotions, such as happiness, and strengthened psychological resources, such as psychological resilience (Fredrickson, 2004). According to BBT, these two factors—happiness and psychological resilience—should function sequentially rather than concurrently. Existing studies (Gruber et al., 2013) suggest that when happiness as a positive emotion is variable over time, individuals have poorer psychological health. Likewise, stable positive emotions over time can increase the repertoire of psychological resources, implying that positive emotions precede the enhancement of personal resources, rather than occurring simultaneously (Gruber et al., 2013). These concepts of happiness and psychological resilience are now under scrutiny in relation to existing evidence from both BBT and the tourism literature to form the basis for H2.
Unlike the overarching principles of BBT suggesting that an experience of emotion such as happiness should precede and sequentially increase personal resources such as psychological resilience, empirical evidence in the travel context is lacking. Instead, happiness and psychological resilience have been studied independently within both the BBT framework and tourism literature, except for the study of Pocinho et al. (2022). Similarly, their role as potential mediators in the enhancement of QoL or other positive psychology indicators is lacking. Existing literature demonstrate that emotions and psychological resilience can function as serial mediators individually when considered alongside other tourism concepts (Li et al., 2022; Mulcahy et al., 2023; Wu & Lau, 2022). For instance, emotions have been found to mediate the impact of threat appraisals on travel avoidance (Wu & Lau, 2022), while psychological resilience has mediated tourism well-being during crises such as COVID-19 (Mulcahy et al., 2023).
While it is evident that positive emotions and psychological resilience can individually contribute to explaining tourist behavior and well-being within serial mediation models (Mulcahy et al., 2023; Wu & Lau, 2022), their integrated examination in relation to the relationship between travel frequency and QoL, and aligned with BBT principles, remains lacking. By considering them as serial mediators, we suggest that positive emotions such as happiness can lead to psychological resilience, thereby providing a potential explanation for why increased leisure travel frequency correlates with higher levels of QoL among tourists.
Happiness
The first mechanism explaining why higher leisure travel may be associated with higher QoL for tourists is due to frequent travel offering individuals opportunities to engage in enjoyable and fulfilling experiences, fostering positive emotions such as happiness. However, happiness unlike other positive emotions is particularly unique and discrete in comparison to other positive emotions such as joy, gratitude, and amusement (Linley et al., 2016; McIntyre et al., 2024). Based on empirical evidence, happiness is a broader and more enduring emotional state associated with life satisfaction (Gruber et al., 2013). Consequently, happiness can often have a higher level of certainty (longevity; Aeron & Rahman, 2023) and be felt more intensely than other positive emotions such as amused (Linley et al., 2016).
In the literature, studies grounded in BBT have demonstrated the importance of happiness in improving QoL and related positive psychology indicators (Cohn et al., 2009; Kwon & Lee, 2020; Mitas & Kroesen, 2020). For instance, the work of Cohn et al. (2009) demonstrates how happiness can increase life satisfaction, and this is due to building resilience. However, their work does not take into account how these chains of relationships between happiness, resilience, and life satisfaction or QoL, can be associated or enhanced by leisure travel. More specifically related to tourism, Kwon and Lee (2020) evidence how travel prolongs individuals’ experience of happiness. Mitas and Kroesen (2020) also demonstrate that higher vacation frequency leads to higher reported positive affect, including happiness. Yet, Kwon and Lee (2020) and Mitas and Kroesen (2020) do not elucidate how happiness may build psychological resilience and subsequently have an association with QoL. This research therefore seeks to address this gap in tourism studies and the application of BBT in this field to show how, as evidenced albeit separately, leisure travel can be associated with happiness (Kwon & Lee, 2020; Mitas & Kroesen, 2020) and that happiness can build and/or be associated with higher levels of psychological resilience (Cohn et al., 2009).
Psychological Resilience
Next, the role of psychological resilience as the following second mechanism (mediator) is considered, which can be defined as a personal resource used by individuals to maintain their well-being and adapt during stressful events (Fletcher & Sarkar, 2013; Prayag et al., 2020).
Of the psychological resources considered in BBT, resilience is a known driver of several positive outcomes, such as wellbeing and life satisfaction (Cohn et al., 2009). Thus, considering this, the current study seeks to explore, consistent with this literature and theorizing, that assuming the aforementioned associations between leisure travel frequency and happiness, and happiness and psychological resilience exist, psychological resilience would then subsequently be associated with higher QoL, completing the chain of relationships between the concepts of interest to the current study.
The concept of resilience is a growing area of interest for tourism scholarship. Much like QoL, resilience has been studied from different perspectives, such as the resilience of tourist destinations (Traskevich & Fontanari, 2023), tourism operators (Prayag et al., 2020), and destination residents (Su et al., 2023). However, considerations of how psychological resilience is built or supported in tourists specifically have been somewhat less of a focus (Gottschalk et al., 2022). There has been debate and varying conceptualizations regarding psychological resilience, whether it is a stable trait or changeable state of an individual (Lock et al., 2020). While the current research acknowledges there are arguments for psychological resilience as a trait (moderator) or state (mediator), given the theoretical underpinning of the current research being BBT, the current research is situated in considering it as a mediator, which is enhanced via positive emotions, namely happiness.
For instance, Prayag (2023) demonstrated that travel motivation, which includes the factors of socialization, exploration, and escapism, positively influences psychological resilience. The work of Han and Patterson (2007) also lends support for the ability of travel to enhance psychological resilience by demonstrating that engaging in risk activities can reduce stress, thereby building resilience and improving QoL. Other research, such as Mulcahy et al. (2023), also provides evidence of psychological resilience as a key mediator when considering traveling, COVID-19 risk, and well-being. Beyond tourism research, BBT studies demonstrate positive emotions and, in particular, happiness as predictors of psychological resilience (Short et al., 2020). The study of Seaton and Beaumont (2015) shows similar findings, providing evidence that positive emotions enhance ego-resilience and eudaimonic well-being, baring close similarities with the current research considering happiness should enhance psychological resilience, followed by tourist QoL.
Previous research has delved into positive emotions such as happiness and psychological resilience, both within the BBT framework and applied to tourism, offering insights into tourism’s transformative effects. These emotions may explain why higher travel frequency correlates with improved tourist QoL. This study seeks to merge these strands of literature, proposing that, aligned with BBT, increased travel frequency may boost positive emotions like happiness, consequently enhancing psychological resources and QoL. Therefore, the hypothesis is:
Factors Which Influence Tourist Broadening and Building
As indicated in Table 1, few tourism studies have explored factors influencing the extent of individuals’ broadening (initial positive emotion and its impact on cognitive tendencies) and building (benefits of positive emotions on personal resources for enhanced well-being and adaptive functioning). This research aims to propose two factors that could alter the strength of the relationship between leisure travel frequency, happiness, psychological resilience, and QoL based on individuals’ pre-existing personal resources. For instance, individuals with high (low) existing personal resources may experience fewer (greater) broadening and building benefits from travel frequency on QoL. To shed light on this, the study explores coping ability and perceived vulnerability as moderators, variables influencing the strength or direction of the relationship between travel frequency and QoL.
Tourist Coping Ability
In this study, coping is defined as individuals’“cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person” (Lazarus & Folkman, 1984, p.141). In the tourism literature, coping has been shown to provide insights into a variety of tourism-related phenomena, including residents’ responses to tourism development (Jordan et al., 2015) and experiences with dark tourism sites (Jordan & Prayag, 2022). Such studies often consider coping as a strategy whereby specific techniques and behaviors are undertaken by individuals to manage adverse situations. For instance, Jordan and Prayag (2022) demonstrated that tourists engaged in either problem-focused or emotion-focused coping strategies when responding to their cognitive and emotional appraisals of a dark tourism experience.
A perspective complementary to coping, known as “coping ability” or “coping flexibility” (Folkman & Moskowitz, 2004), is also considered in this study. Coping ability focuses on the overall capacity to manage and adapt to stressful situations (C. Cheng et al., 2014). Unlike coping strategies, which are specific techniques and behaviors, an individual’s coping ability is influenced by factors outside and prior to a stressful situation, such as personality traits, culture, age, and past experiences (C. Cheng et al., 2014; Duhachek & Iacobucci, 2005). Those with a well-developed coping ability draw on these factors to better equip themselves to deal with stressful situations. Conversely, those with a weak coping ability may struggle to cope with stressful situations.
Beyond the usual stressors in tourism literature, BBT highlights the advantages of positive emotions in boosting personal resources. According to Fredrickson (2001), these experiences enhance mood and enrich cognitive and social abilities. Frequent travel, especially for those with limited initial capabilities, may significantly broaden and enrich personal resources. Hence, the following hypothesis is suggested:
Tourist Vulnerability
In the tourism literature, vulnerability has been examined from various angles, including its contributing factors (Mulcahy et al., 2023), the vulnerability of travel destinations (Duro et al., 2021), and its implications for the broader tourism industry (Scott et al., 2019). The current research focuses on tourists’ vulnerability, defined as “unique and subjective experiences where characteristics such as states, conditions, and/or external factors lead to a consumer [tourist] experiencing a sense of powerlessness in consumption settings” (Riedel et al., 2021, p.110).
Understanding tourists’ vulnerability is crucial in tourism scholarship as it significantly influences behavior, decision-making, and experiences (Riedel et al., 2021), thereby informing policy and marketing strategies (Mulcahy et al., 2023). However, research on tourist vulnerability in tourism remains relatively scarce compared to other business disciplines. Recent literature has begun exploring vulnerability from deficit and strength-based perspectives (Fisk et al., 2023), challenging its traditional negative connotation. By drawing on BBT (Fredrickson, 2001) to understand how the concepts embedded in this study interact, we aim to adopt a strength-based and positive psychology perspective on how adversity triggers positive outcomes through travel experiences.
Highly vulnerable tourists may benefit more from travel due to their heightened need for positive emotions and psychological resilience. Research suggests that individuals facing significant stress or adversity may have lower levels of these qualities (Fredrickson, 2001; Ong et al., 2006). According to BBT (Fredrickson, 2001), travel can provide opportunities for positive emotional experiences and personal growth, particularly for highly vulnerable individuals who may lack such opportunities in their daily lives. For instance, those coping with chronic illness or trauma may have fewer chances for enjoyable activities. Travel may thus amplify its impact on QoL for highly vulnerable consumers by fostering higher positive emotions and resilience. Therefore, based on this reasoning and the discussion of vulnerability, the following hypothesis is proposed:
In summary and visual representation of the hypotheses, the conceptual model underpinning the network of relationships to be tested in the current research is presented in Figure 1.
Conceptual model.
Overview of Studies
This research comprises three studies conducted between 2020 and 2023 (see Table 2), utilizing samples of Australian tourists from three distinct survey panels: Qualtrics, Dynata, and Prolific. This methodological choice aligns with Goodman and Paolacci’s (2017) recommendations for testing theories across diverse samples.
Overview of Studies.
Study 1 investigated the relationship between travel frequency and quality of life (QoL), exploring the moderating effects of coping mechanisms and the mediating roles of happiness and psychological resilience. Conducted during the peak of the COVID-19 pandemic, Study 1 may have been influenced by prevailing travel restrictions. In Study 2, the focus remained on the relationship between travel frequency and QoL, emphasizing the moderating influence of vulnerability, with happiness and psychological resilience as mediators. This study was conducted during the pandemic’s later stages, characterized by relaxed but still present travel restrictions. Study 3 explored the moderating roles of coping and vulnerability, employing varied measures of happiness while reaffirming psychological resilience as a mediator. This study aimed to validate the full conceptual model and theoretical framework, employing rival models and testing various emotional responses to ensure robustness in both theory and empirical evidence.
Overall, the research design adheres to recommendations for assessing the generalizability of findings across different sample panels of Australian tourists, spanning market research companies and crowdsourcing platforms (Goodman & Paolacci, 2017). The consistent findings across these panels underscore the robustness of the results, mitigating concerns that observed impacts were solely due to timing and the profound disruptions caused by COVID-19 on travel behavior, the tourism sector, and individual well-being (Assaf et al., 2022; Mulcahy et al., 2023).
Study 1: Coping
The aim of Study 1 was to generate preliminary insights into the effects of leisure travel frequency on QoL and identify potential mediators (such as happiness and psychological resilience) and moderators (such as the ability to cope) that could influence this relationship.
Method
Study Setting and Justification
Data for Study 1 were collected in Australia over a 14-day period from 29th September to 12th October 2020. Respondents were asked to report the leisure trips taken within the 4-month period leading up to their survey participation date, which corresponded to late May to early October 2020. It is important to note that by the end of March 2020, international and domestic travel was restricted in Australia, but by early June, domestic travel for holiday purposes was once again permitted, subject to specific conditions. New South Wales allowed holiday travel within the state from 1st June 2020, while Queensland allowed recreational travel within 250 km from 12th June 2020 (Storen & Corrigan, 2020), and domestic intra- and inter-state travel started to increase in most Australian states and territories from June 2020.
Understanding how travel enhanced QoL during the COVID-19 pandemic, was appropriate for the following reasons. Firstly, the pandemic and associated restrictions had significant impacts on mental health and well-being, including increased stress, anxiety, and depression (Salari et al., 2020). Therefore, identifying activities or behaviors that could improve well-being during this time would be valuable information for future crises, such as other pandemics.
Data Collection and Instrument Development
An online survey was conducted using Qualtrics, a global survey panel provider company, to collect the data. The purposeful sample consisted of Australian residents 18 years and older. The majority of the sample was female (60.9%), aged between 33 and 56 years (31.7%), with an average annual income of A$52,000 to A$77,999. All items in this study were measured using previously validated scales from the literature.
QoL was measured using the three-item scale of Sweeney et al. (2015; seven-point Likert scale, 1 = strongly disagree, 7 = strongly agree). This scale was considered appropriate since it measures individuals’ life satisfaction, which aligns with the QoL indicator previously justified as the core focus of the current research.
The measurement of happiness utilized two items from the literature, assessed on semantic differential scales. Initially, we employed the single-item measure adapted from the scale developed by Gurin et al. (1960), utilized in studies assessing predictions of happiness and its impact on depression (H. Cheng & Furnham, 2003). To address concerns regarding single-item scales, we supplemented this measure with Andrews and Withey’s (1976) delighted-terrible semantic measurement, also widely used to gauge levels of happiness and life satisfaction (Lyubomirsky & Tucker, 1998; Valois et al., 2020). Participants were asked specifically asked, “Taken all together, how would you say you have felt during the last 4 months (ranging from very unhappy to very happy), and in the past 4 months, how did you feel about how happy you are (ranging from terrible to delighted)?” These items, once confirmed to be reliable and valid for use as a multi-item scale, were then combined to create an index of happiness score.
Psychological resilience was measured using items adapted from the Connor–Davidson Resilience Scale (Campbell-Sills & Stein, 2007; seven-point Likert scale, 1 = strongly disagree, 7 = strongly agree). This scale was chosen given its proven ability to be adapted for tourism studies and functioning as a mediator within these studies consistent with the aim of the current research (e.g., Mulcahy et al., 2023; Zheng et al., 2021).
To measure leisure travel frequency, participants were asked, “In the past four months, how many trips have you taken for a holiday or leisure travel?” Participants indicated their response by entering a number into an open text box. This method of measuring leisure travel frequency aligns with the approach used by Zheng et al. (2022), who employed a tourism intensity measure based on the number of visits or stays away from home.
Control Variables and Common Method Bias
To ensure robustness and rigor in our analysis, we conducted checks for control variables and common method bias. Sample characteristics such as employment status, education, relationship status, and income were included as covariates to control for potential confounding effects. This approach allowed us to eliminate alternative explanations for factors predicting or enhancing QoL beyond our hypotheses, thereby improving the accuracy of our estimates. Notably, during the COVID-19 pandemic, employment, income, and relationship status were identified as significant factors influencing individuals’ QoL and well-being (Assaf et al., 2022).
To mitigate the impact of common method bias (CMV) on the results, several strategies were implemented. Following Podsakoff et al. (2012) recommendations, diverse response options were utilized alongside question randomization. Additionally, to comply with ethical guidelines, the survey ensured anonymity and confidentiality for all participants. A Harman’s single factor test, widely employed in tourism research (Kock et al., 2021), assessed the potential influence of CMV on the findings, revealing that a single factor explained 44.24% of the variance, below the 50% threshold. Given the study’s emphasis on examining moderation and mediation effects, it is pertinent to note findings by Siemsen et al. (2010), indicating that CMV does not inflate interaction effects.
Results
Instrument Validation
Prior to testing the hypotheses, the constructs were assessed for reliability and validity. Firstly, the measurement model was assessed using confirmatory factor analysis. The measurement model was shown to have a good fit to the data (CMIN/DF = 2.61, comparative fit index [CFI] = 0.975, root mean square error of approximation [RMSEA] = 0.05, and standardized root mean square residual [SRMR] = 0.04). Furthermore, the constructs were shown to have strong reliability and validity, as detailed in Appendix 1.
Hypothesis Testing
To test H1, we utilized the PROCESS extension of SPSS with Model 1 and 5,000 bootstrapping samples. The independent variable was leisure travel frequency, moderator was coping ability, and the outcome was QoL. The covariates of income, education, gender, relationship status and age were also included. The results are summarised in Table 3. The results showed that leisure travel frequency had a direct positive association with QoL (B = 0.973, SE = 0.31, p = .000), supporting H1. Further, the interaction between leisure travel frequency and coping ability was significant (B = −0.18, SE = 0.06, p = .004). The spotlight analysis showed that the effect of leisure travel frequency was significant and strongest for those with low coping ability (B = 0.262, SE = 0.077, p = .000), followed by those with moderate coping ability (B = 0.14, SE = 0.05, p = .007). For those who identified as having high coping ability the association of leisure travel frequency on QoL was non-significant (B = 0.02, SE = 0.06, p = .748).
Study 1 and Study 2 Results.
To assess H2 and H3, the data were analyzed using the Model 85 template with 5,000 bootstrapping samples (see Table 3). The independent variable was leisure travel frequency, mediators including happiness and psychological resilience, the outcome variable was QoL, and the moderator was coping ability. The same covariates as tested in H1 were again used in the moderated mediation analysis. The index of moderated mediation was significant (index = −0.004 SE = 0.002, LCI = −0.011, UCI = −0.000).
The indirect effect of leisure travel frequency on QoL via the mediators of happiness and psychological resilience was significant and strongest for individuals identifying as having low coping ability (B = 0.007, SE = 0.003, LCI = 0.001, UCI = 0.015). This indirect effect was significant but weaker for individuals with moderate coping ability (B = 0.004, SE = 0.002, LCI = 0.005, UCI = 0.009) and was evidenced to be non-significant for individuals identifying as having high coping ability (B = 0.000, SE = 0.002, UCI = −0.005, UCI = 0.005). These findings corroborate H2, indicating that happiness and psychological resilience serve as mediators in the connection between leisure travel frequency and QoL, particularly among individuals who self-identified with moderate to low levels of coping ability, rather than high coping ability, thus supporting H3 in turn.
Study 2: Vulnerability
The purpose of Study 2 was to explore the same mediated relationships as in Study 1, but with a focus on how the strength of these relationships may vary based on vulnerability rather than coping ability.
Method
Study Setting, Data Collection, and Instrument Development and Validation
Study 2 was conducted between 26th April 2022 and 4th May 2022, replicating the research design of Study 1, and surveying a sample of 290 Australian consumers with the same survey instrument and survey software Qualtrics. Participants were recruited through the survey panel provider, Dynata. In the sample, 49.7% identified as female, 37% reported working full-time, 34% identified undergraduate university studies as their highest completed form of education, and 38.7% were married.
At the time of the study, the Australian government had relaxed travel restrictions, allowing unrestricted domestic and international travel across most states and territories, except for individuals from specified COVID-19 hotspots who still required quarantine or permits. This setting was ideal for re-examining the relationships identified in Study 1 for several reasons. As global conditions gradually normalized, there was a noticeable resurgence in people’s desire to travel and participate in leisure activities previously restricted. Understanding how travel impacts QoL can assist individuals in making informed travel decisions and maximizing their experiences. Furthermore, investigating these relationships during a later phase of the crisis can validate their applicability and uncover how they evolve over time. Study 2, conducted during eased travel restrictions, offered valuable insights into the dynamics between travel and QoL in a post-COVID-19 era.
All constructs’ measurements remained consistent with Study 1 except vulnerability was considered instead of coping ability. Vulnerability was tested using the six-item psychological vulnerability scale of Sinclair and Wallston (1999).
Control Variables and Common Method Bias
Study 2 followed identical procedures to Study 1 for controlling variables and CMV. We controlled for sample characteristics including employment status, education, relationship status, and income as covariates. CMV was addressed through randomized survey item placement and ensuring respondent confidentiality. Harman’s single factor test indicated that items explained 40.83%, below the 50% threshold, reducing CMV concerns. Interaction effects of vulnerability, central to the study, were evaluated following Siemsen et al. (2010) and Podsakoff et al. (2012) guidelines, ensuring any significant findings were not influenced by CMV.
Results
Instrument Validation
Prior to testing the hypotheses, the constructs were assessed for reliability and validity. Firstly, the measurement model was assessed using confirmatory factor analysis. The measurement model was shown to have a good fit to the data (CMIN/DF = 1.73, comparative fit index [CFI] = 0.969, root mean square error of approximation [RMSEA] =0.05, and standardized root mean square residual [SRMR] = 0.04). Furthermore, the constructs were shown to have strong reliability and validity, as detailed in Appendix 1.
Hypothesis Testing
The data were analyzed using with the Model 85 template with 5,000 bootstrapping samples (see Table 4). The independent variable was leisure travel frequency, mediators including happiness and psychological resilience, the outcome variable was QoL, and the moderator was coping ability. The same covariates as Study 1 were again used in the moderated mediation analysis. The index of moderated mediation was significant (index = −0.004 SE = 0.002, LCI = −0.011, UCI = −0.000). The indirect effect of leisure travel frequency on QoL was significant and strongest for those who identified having high levels of vulnerability (B = 0.066, SE = 0.020, LCI = 0.030, UCI = 0.109). The indirect effect weakened but remained significant for individuals identifying as having moderate levels of vulnerability (B = 0.039, SE = 0.014, LCI = 0.014, UCI = 0.069). The indirect effect was non-significant for individuals who identify as having low levels of vulnerability (B = 0.016 SE = 0.013, LCI = −0.007, UCI = 0.045). Taken together these results provided support for H2 and H4 showing that happiness and psychological resilience functioned as serial mediators for the association between leisure travel frequency and tourist QoL, and that tourist vulnerability levels moderated this relationship.
Study 3 Results.
Study 3: Coping, Vulnerability, and Isolating Happiness as A Positive Emotion
Study 3 again aimed to examine the effect of travel frequency on QoL. However, to extend beyond the parameters of Study 1 and Study 2, and rule out potential competing theoretical explanations, another two emotions (love and anger) beyond happiness were also included to ensure that this indeed was the emotion explaining the association between leisure travel frequency and QoL.
Method
The data were collected on 21st March 2023 using Qualtrics as the survey platform when the impacts of COVID on travel had reduced to lend generalizability of the findings outside the impact of a pandemic. Furthermore, to recruit the participants, the survey panel provider Prolific was utilized.
Study Setting and Data Collection
We recruited 379 Australian participants on the crowdsourcing platform Prolific (Mage = 32.00, SD = 12.30). In the sample, 52% identified as female, 51% reported working full-time, and 44% identified undergraduate university studies as their highest completed form of education. Participants were recruited and participated in February 2023 in exchange for financial compensation. This approach was considered appropriate and valuable because it enabled the study to determine whether the relationships identified in Study 1 and Study 2, which were relevant during the peak and mid-late periods of the COVID-19 pandemic, could also apply in the later and post-pandemic stages.
Using the same procedure as Study 1 and 2, participants were informed about the purpose of the study and provided information detailing the ethical requirements of the study and the need to indicate their consent to participate. Once participants indicated their consent to participate, they were asked about their recent travel behavior, emotional states, coping, vulnerability, psychological resilience, and QoL. The survey concluded with demographic questions relating to age, gender, income, and employment.
Control Variables and Common Method Bias
As per Study 1 and Study 2, the sample characteristics of employment status, education, relationship status, and income, were controlled for within the analysis as covariates, to rule out their potential confounding impact on the results. CMV was addressed by employing randomized survey questions and ensuring participant confidentiality. Study 3 included an attention check item requiring participants to respond with “strongly agree” to confirm attentiveness; two participants failing this were excluded from analysis. A Harman’s single factor test indicated that a single factor explained 34.8% of variance, suggesting CMV was not significant. Moreover, given the study’s focus on interaction effects, CMV was unlikely to distort the findings (Podsakoff et al., 2012; Siemsen et al., 2010).
Results
Instrument Validation
The self-report measures for QoL, psychological resilience, coping, and vulnerability, were included in Study 3 as per Studies 1 and 2. Different to Study 1 and 2, a range of emotions were measured including happiness, love, and anger, with items adapted from Northey et al. (2020) who utilized a range of discrete emotions to isolate and rule out competing emotional states as key explanator mechanisms. For the happiness measure, consistent with Northey et al. (2020) we employed the items “happy” and “amused.” Participants were asked to indicate, on a 9-point semantic differential scale ranging from 1 (not at all) to 9 (extremely), how frequently they experienced these emotions over the last year (March 2022 to March 2023). Afterward, we calculated a happiness index score derived from their responses. Additionally, we evaluated other emotions such as love (affection, fondness) and anger (irritation, rage), computing their respective scores to establish index scores for inclusion in the robustness tests. This procedure mirrors the approach adopted by Van Esch et al. (2022) in their examination of political ideology and tourist responses to AI, encompassing emotional reactions as well. Prior to testing the hypotheses, the constructs were assessed for reliability and validity. Firstly, the measurement model was assessed using a confirmatory factor analysis. The measurement model was shown to have a good fit to the data (CMIN/DF = 2.22, comparative fit index [CFI] = 0.947, root mean square error of approximation [RMSEA] = 0.05, and standardized root mean square residual [SRMR] = 0.04). Further, as shown in Appendix 1, reliability thresholds were also confirmed.
Results
To test for a moderated serial mediation, the PROCESS extension of SPSS was used with the Model 85 template with 5,000 bootstrapping samples. Two models were run with the moderators, with coping and vulnerability being alternated in and out as the moderator. A summary of the model results is presented in Table 4.
Model 1: Coping as a Moderator
In the coping model, the index (index = −0.003, SE = 0.002, LCI = −0.008, UCI = −0.000) indicated that individuals who identified with low coping ability (B = 0.005, SE = 0.002, LCI = 0.000, UCI = 0.011) had the strongest significant indirect effect on QoL. This effect weakened for those in the moderate coping ability group (B = 0.002, SE = 0.001, LCI = 0.000, UCI = 0.006) and became non-significant for those in the high coping ability group (B = −0.000, SE = 0.00, LCI = −0.002, UCI = 0.001).
Model 2: Vulnerability as a Moderator
In the vulnerability model, the index of moderated mediation was significant (index = 0.005, SE = 0.003, LCI = 0.000, UCI = 0.012). Those who identified as having high vulnerability had a significant and the strongest indirect effect (B = 0.027, SE = 0.008, LCI = 0.012, UCI = 0.046). For those who identified as having moderate vulnerability, the indirect effect weakened (B = 0.020, SE = 0.006, LCI = 0.010, UCI = 0.034), and this effect further weakened for those who identified as having low vulnerability (B = 0.012, SE = 0.005, LCI = 0.010, UCI = 0.034).
Robustness Testing and Rival Models
In Study 3, we sought to rule out potential competing explanations and test the robustness of the theorizing and hypotheses presented previously. These rival models including reversing the order of the mediators (psychological resilience preceding happiness), as well as alternating happiness with other positive emotional responses (love) as well as negative emotions (anger). This also aligns with the recommendations of Hosany et al. (2021), who suggested that efforts should be made to test competing models to understand the interplay and hierarchy of emotions in tourism studies. All rival models were conducted including coping ability as the moderator.
When testing the first model, whereby the order of happiness and psychological resilience was alternated comparatively to the hypothesized model, the index of moderated mediation was non-significant (index = 0.002, SE = 0.002, LCI = −0.007, UCI = 0.001). The rival model whereby happiness was replaced with the emotion of love was also non-significant (index = −0.0002, SE = 0.008, LCI = −0.001, UCI = 0.001), and so too the rival model using anger (index = 0.000, SE = 0.000, LCI = −0.001, UCI = 0.002). Given the results of the competing models were non-significant, the data indicated that the inclusion of happiness (as opposed to love or the suppression of anger) as the emotional response preceding psychological resilience (as opposed to the alternative positioning where psychological resilience) is more appropriate both empirically and theoretically from the perspective of BBT.
Further, considering the potential differences in intensity and endurance between “happy” and “amused,” despite their use by Northey et al. (2020) as a happiness index, we also conducted models using a single-item measure focusing solely on “happy”. The results were consistent across both coping with significant index of moderation scores (index = −0.001, SE = 0.001, LCI = −0.005, UCI = −0.000) and vulnerability (index = 001, SE = 0.001, LCI = 0.000, UCI = 0.006) models and the indirect effects following a consistent pattern of indirect effect results as per the main hypothesis testing using Northey et al. (2020) happiness index.
Discussion and Implications
This study sought to answer two research questions in relation to QoL. First, it sought to determine whether increased leisure travel can improve QoL through happiness and psychological resilience; the findings confirmed that indeed the central tenets of BBT is applicable as tourists use positive emotions to cope and grow from travel experiences. Second, the study sought to determine whether pre-existing psychological capacity factors (coping ability and perceived vulnerability; see Figure 1) can enhance or diminish the QoL benefits of travel, which demonstrated that different levels of coping and vulnerability interplays with QoL in different ways. Nonetheless, across all three studies, the findings supported the four tested hypotheses and provide important theoretical and managerial implications.
Theoretical Implications
The results contribute theoretically to the tourism literature in three ways. Firstly, it provides more depth into the mechanisms by which leisure travel frequency into QoL benefits for tourists and isolate the underlying reasons. While prior research has generally supported the notion that travel enhances QoL (Chen et al., 2016; Neal et al., 2007), studies on travel frequency (Zheng et al., 2022) have predominantly focused on demonstrating a direct effect without delving into the mediating processes that elucidate this relationship. The findings supporting H1 and H2 affirm the idea that heightened travel frequency can indeed result in QoL improvements under specific conditions, driven by tourists’ positive emotions (such as happiness) and psychological resources (like psychological resilience), aligning with the theoretical framework of BBT utilized in this study.
These results collectively enrich the QoL and tourism literature by advancing beyond the more traditional theories like cognitive appraisal theory and deficit-based theories such as the transactional model of stress (Jordan et al., 2015, 2019; Jordan & Prayag, 2022), which primarily concentrate on the cognitive precursors of emotions that arise from stressful tourism situations. Instead, this study adopts a more strength-based perspective via BBT, in alignment with the positive psychology call in tourism studies (Filep & Laing, 2019), where the role of positive emotions is viewed as a mechanism to foster and elevate human flourishing triggered or experienced by tourism and travel experiences. This is evidenced in the current research by the observed higher levels of psychological resilience and QoL in the current study.
Secondly, this research contributes to the growing BBT literature within tourism, as well as broader tourism studies that delve into happiness and psychological resilience. As illustrated in Table 2, previous studies have seldom simultaneously explored both the positive emotional responses and the psychological resources aspects of BBT to elucidate tourism experiences (Kwon & Lee, 2020; Mitas & Kroesen, 2020; Mulcahy et al., 2023; Su & Swanson, 2020). Thus, while the current literature draws from BBT, the existing studies have yet to fully embrace its dimensions collectively in a single study. We demonstrate the collective effect of psychological resources (emotions, resilience, coping and vulnerability) via different pathways on QoL. Both happiness and psychological resilience are mediators in the relationship between travel frequency and QoL for tourists, implying they transform experiences into long-term benefits such as QoL. Moreover, these findings offer potential explanations for studies like Zheng et al. (2022), which lacked clarity in explaining why tourism intensity benefits individual well-being.
Thirdly, the insights provided by the moderating roles of coping and vulnerability in shaping the relationship between travel frequency and QoL extend both BBT and the tourism literature. By showing how these factors intervene to lessen QoL benefits for specific groups, this study extended the traditional focus on demographic factors (Zheng et al., 2022) and destination-based considerations commonly used to explain the benefits of travel on QoL (Su et al., 2023), highlighting the importance of taking a more psychological perspective to understand how tourists’ pre-conditioned psyches and capabilities may impact their travel experiences and QoL. Through spotlight moderation analysis, this research identified the levels of coping and vulnerability at which the relationship between travel frequency and QoL became significant or non-significant. Thus, the results of H3 and H4 reiterate that tourists benefit most from higher travel frequency if they have weak coping abilities or feel greater vulnerability, but this effect weakens as coping abilities increase (vulnerabilities decrease). By considering the importance of coping and vulnerability concurrently, this study contributes to tourism scholarship by demonstrating how these factors are crucial considerations in understanding the heterogeneity of travel frequency on QoL through a set of psychological factors: coping, emotions, psychological resilience, and vulnerability. The results highlight the need for nuanced analyses to pinpoint when such factors play a significant role, by considering groups with high/moderate/low levels of coping and vulnerability. In this way, the results advance those of prior research (Espiner & Becken, 2014; Jordan et al., 2015; Jordan & Prayag, 2022) that mostly examine the main effects of coping and vulnerability.
From a methodological perspective, this research contributes to the tourism literature by examining the moderated-mediation effects of a range of psychological factors. These factors have not previously been considered concurrently in QoL tourism studies focused on either residents or tourists (see Table 2). Additionally, there appears to be a lack of rigor and sophisticated analysis in tourism research regarding the concurrent testing of multiple serial mediating mechanisms, such as happiness and psychological resilience, evidenced in the current study. Studies of BBT (see Table 1) do not always conduct serial mediation analyses or connect or test both positive emotions and psychological resources, which can be limiting in terms of explaining whether both are necessary mechanisms for explaining the effect of a stimulus on an outcome, as well as providing a more comprehensive test of the theory. Likewise, spotlight analyses, in which outcomes are evaluated on different levels of a continuous moderator (such as coping ability and vulnerability in the current study), are notably scarce in tourism studies, whereas this approach is being increasingly utilized in psychology and marketing studies (Krishna, 2016). It is hoped that by demonstrating the utility of conducting both mediation and spotlight analyses together, greater theoretical and practical insights can be drawn for future tourism research.
Practical Implications
This research also has important practical implications for a range of stakeholders, such as tourists, destination marketers, governments, and tourism businesses. The first practical implication relates to the finding that tourists who perceive themselves as more vulnerable are those who will benefit most from travel if tourism industry professionals can (a) design and tailor their services and experiences to cater to these tourists’ needs; (b) position existing experiences to highlight their positive psychological benefits (e.g., health and wellness); and (c) collaborate with tourism industry stakeholders to develop niche tourism activities and experiences that focus on the resilience building of individuals. For example, tourism service providers could develop programs or activities to enhance tourists’ feelings of security and control, such as offering guided tours or providing detailed information about a destination’s safety measures. Such measures could help alleviate tourists’ concerns about their vulnerability and promote a sense of comfort and security. A further recommendation is to offer specialized support services (e.g., airport pickups, hotel transfers, and assistance with itineraries) that help reduce stress and potentially encourage higher travel frequency.
Second and expanding further on how tourism industry professionals can utilize the documented health benefits of regular responsible travel, marketing campaigns could emphasize the promotion of more frequent trips that are closer to home, even if they are shorter in duration. This approach aligns with the findings of this study, which indicate that such travel patterns are likely to enhance both happiness and QoL. By encouraging travelers to take shorter but more frequent trips that are closer to home, tourism professionals can effectively communicate the potential long-term benefits of travel on well-being but also mitigate increasing concerns for irresponsible travel by those who travel frequently, thereby fostering a sustainable and positive impact on individuals’ happiness and QoL. This strategy could also aid in responding to potential preferences for flexibility and spontaneity in travel but also supports broader goals of promoting health and well-being and responsible travel through tourism experiences.
Third, understanding that happiness and psychological resilience are crucial factors contributing to QoL through travel provides valuable insights into supporting tourism as an economic activity. Designing travel experiences that promote adventure and novelty can elicit positive emotions that enhance psychological resilience. Marketing efforts can focus on boosting tourists’ confidence, while tourism operators can offer activities like hiking, kayaking, or rock climbing, tailored for beginners to provide adventure and challenge. Considering varying coping levels and perceptions of vulnerability, operators should provide beginner-level activities and support tourists with scaffolded experiences to create memorable journeys. These activities should be enjoyable and uplifting, fostering happiness and resilience without undue stress. Alternatively, targeting relaxation for tourists with weaker coping skills or greater vulnerability through small-group settings, personalized services, or serene environments can enhance positive emotions and bolster psychological resilience.
Fourth, the findings of this study hold implications and considerations for policy makers and mental health professionals alike. Mental health is recognized as a critical issue in government and healthcare sectors, with mental health practitioners playing a frontline role in addressing these challenges. Building on the evidence from this research, policymakers could leverage these findings to advocate for investments in infrastructure and policies that promote more frequent responsible travel opportunities closer to home for citizens. Such initiatives could potentially contribute to improving mental well-being by offering individuals opportunities to rejuvenate and experience positive emotions through travel. Moreover, mental health practitioners could integrate responsible travel recommendations into their wellness programs. By advising clients on the psychological benefits of regular getaways, practitioners can support efforts to mitigate stress and enhance overall life satisfaction. This proactive approach aligns with promoting holistic health practices and underscores the role of travel in fostering resilience and mental well-being. Together, these strategies highlight the potential synergy between public policy, mental health advocacy, and promoting positive lifestyle choices through travel.
Limitations and Future Research Directions
While this research has some key strengths, such as the collection of tourist data across different stages during and toward the end of the COVID-19 pandemic, as well as the testing of different rival model structures, it also has limitations that provide opportunities for future research.
While this research utilized a robust methodology, with three samples across three different time points, it is important to note that the participants were exclusively Australian tourists, affecting the potential generalizability of the findings to tourists in other countries. As tourists from different countries may have varying personalities, cultural backgrounds, and perceptions, it is crucial for future research to examine the applicability of the proposed model in different tourist markets. Likewise, the COVID-19 experience for Australia was very different to that of the rest of the world, where strict lockdowns might have generated pent-up demand, leading to higher travel frequency as restrictions eased. Third, the COVID-19 experience of Australians may also have significant implications for the coping and vulnerability experienced and reported through this study.
While this research offers a more comprehensive explanation of why leisure travel enhances tourists’ QoL than prior literature, it’s crucial to note its focus on one indicator: life satisfaction (Sweeney et al., 2015), and one measurement of leisure travel frequency (the number of trips taken), leaving room for future exploration. As discussed earlier, QoL indicators are multifaceted, encompassing economic, social, and psychological factors. Utilizing multidimensional frameworks or measurements could deepen our understanding of the leisure travel-QoL association. Determining whether higher leisure travel frequency correlates with all or most QoL indicators, or only select ones, would be valuable in discerning the boundary conditions of this association.
Regarding leisure travel frequency, while this research demonstrated its positive association with QoL (specifically life satisfaction), it does not explain whether the duration of a trip or its purpose (e.g., visiting family, adventure) plays a role. Future studies could build on these findings by investigating whether trip duration or travel motivation further explains the leisure travel-QoL association. For instance, research could explore whether a combination of different types of travel is necessary, or if higher frequency but shorter trips yield more significant benefits.
Whilst the current study has strengths in examining the relationships within its framework across three different time points and three distinct samples, it also presents limitations that pave the way for future research endeavors. One such limitation is the inability to employ longitudinal analysis techniques due to the distinct nature of the samples across the three studies. Future research could aim to utilize the current framework with longitudinal designs to explore the longitudinal effects of leisure travel frequency on happiness and psychological resilience, thereby enhancing our understanding of the causal nature of these relationships as well as potential decay effects over time.
Footnotes
Appendix
Scales, Means, SDs of study constructs.
| Construct/Items | Study 1 | Study 2 | Study 3 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Loadings | M | SD | Loadings | M | SD | Loadings | M | SD | |
| Happy 1 (Study 1/2)/Happy (Study 3) | 0.92 | 4.48 | 1.33 | 0.91 | 4.74 | 1.60 | 0.93 | 5.99 | 1.66 |
| Happy 2 (Study 1/2)/Amused (Study 3) | 0.92 | 4.45 | 1.37 | 0.94 | 4.72 | 1.56 | 0.91 | 6.37 | 1.58 |
| AVE | 0.84 | 0.85 | 0.84 | ||||||
| Composite reliability | 0.91 | 0.90 | 0.91 | ||||||
| Psychological resilience | |||||||||
| I am able to adapt when changes occur. | 0.80 | 5.28 | 1.09 | 0.81 | 5.24 | 1.16 | 0.81 | 5.33 | 1.19 |
| I can deal with whatever comes my way. | 0.85 | 5.08 | 1.16 | 0.80 | 5.05 | 1.30 | 0.85 | 4.99 | 1.37 |
| I try to see the humorous side of things when I am faced with problems. | 0.64 | 5.04 | 1.23 | 0.62 | 5.00 | 1.28 | 0.52 | 4.96 | 1.43 |
| Having to cope with stress can make me stronger. | 0.72 | 4.96 | 1.17 | 0.69 | 4.99 | 1.27 | 0.66 | 4.80 | 1.40 |
| I tend to bounce back after illness, injury or other hardships. | 0.77 | 5.23 | 1.14 | 0.81 | 5.06 | 1.29 | 0.80 | 5.01 | 1.37 |
| I believe I can achieve my goals, even if there are obstacles. | 0.81 | 5.13 | 1.10 | 0.75 | 5.16 | 1.15 | 0.76 | 5.18 | 1.29 |
| Under pressure, I stay focused and think clearly. I am not easily discouraged by failure. | 0.81 | 4.99 | 1.23 | 0.80 | 5.01 | 1.38 | 0.74 | 4.79 | 1.36 |
| I am not easily discouraged by failure. | 0.76 | 4.83 | 1.31 | 0.70 | 4.80 | 1.34 | 0.77 | 4.46 | 1.54 |
| I think of myself as a strong person when dealing with life’s challenges and difficulties. | 0.82 | 5.23 | 1.18 | 0.83 | 5.14 | 1.28 | 0.81 | 5.05 | 1.49 |
| I am able to handle unpleasant or painful feelings like sadness, fear, and anger. | 0.74 | 4.98 | 1.23 | 0.74 | 4.98 | 1.35 | 0.64 | 4.97 | 1.28 |
| AVE | 0.64 | 0.57 | 0.77 | ||||||
| Composite Reliability | 0.94 | 0.92 | 0.81 | ||||||
| Coping ability | |||||||||
| Make unpleasant thoughts go away. | 0.86 | 4.37 | 1.15 | - | 0.87 | 4.55 | 1.94 | ||
| Take your mind off unpleasant thoughts. | 0.88 | 4.46 | 1.17 | - | 0.86 | 3.27 | 1.67 | ||
| Stop yourself from being upset by unpleasant thoughts. | 0.89 | 4.43 | 1.18 | - | 0.86 | 4.04 | 2.03 | ||
| Keep from feeling sad. | 0.72 | 4.42 | 1.15 | - | 0.77 | 3.79 | 1.92 | ||
| AVE | 0.71 | 0.75 | |||||||
| Composite reliability | 0.91 | 0.92 | |||||||
| Vulnerability | |||||||||
| If I don’t achieve my goals, I feel like a failure as a person. | - | - | - | 0.60 | 4.32 | 1.98 | 0.88 | 4.55 | 1.94 |
| I feel entitled to better treatment from others than I generally receive. | - | - | - | 0.73 | 4.09 | 1.86 | 0.50 | 3.27 | 1.67 |
| I am frequently aware of fee ling inferior to other people. | - | - | - | 0.70 | 4.06 | 1.86 | 0.85 | 4.04 | 2.03 |
| I need approval from others to feel good about myself. | - | - | - | 0.80 | 3.43 | 1.76 | 0.84 | 3.79 | 1.92 |
| I tend to set my goals too high and become frustrated trying to reach them. | - | - | - | 0.80 | 3.97 | 1.87 | 0.79 | 3.86 | 1.93 |
| I often feel resentful when others take advantage of me. | - | - | - | 0.60 | 4.85 | 1.80 | 0.71 | 5.23 | 1.81 |
| I am happy with the quality of my life. | 0.96 | 4.87 | 1.42 | 0.94 | 4.74 | 1.56 | 0.96 | 4.81 | 1.56 |
| I have a sense of well-being. | 0.87 | 4.93 | 1.39 | 0.91 | 4.85 | 1.49 | 0.85 | 4.96 | 1.42 |
| AVE | - | 0.53 | 0.67 | ||||||
| Composite Reliability | - | 0.83 | 0.90 | ||||||
| Leisure travel frequency | - | 1.80 | 0.97 | - | 2.04 | 1.24 | - | 2.01 | 3.31 |
| QoL | |||||||||
| I am satisfied with the quality of my life. | 0.95 | 4.81 | 1.43 | 0.95 | 4.66 | 1.55 | 0.97 | 4.81 | 1.52 |
| I am happy with the quality of my life. | 0.96 | 4.87 | 1.42 | 0.94 | 4.74 | 1.56 | 0.96 | 4.81 | 1.56 |
| I have a sense of well-being. | 0.87 | 4.93 | 1.39 | 0.91 | 4.85 | 1.49 | 0.85 | 4.96 | 1.42 |
| AVE | 0.91 | 0.87 | 0.83 | ||||||
| Composite Reliability | 0.97 | 0.95 | 0.93 | ||||||
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
