Emotional well-being in peer-to-peer tourism: evidence from thecouchsurfing community

Well-being is a fundamental human need, increasingly recognized in peer-to-peer (P2P) tourism platforms where travelers connect with local hosts to create authentic cultural experiences (Garau-Vadell et al., 2023). Emotional well-being defined by positive emotions such as happiness, contentment and satisfaction has gained notable attention in tourism literature (Wang et al., 2021; Al-okaily et al., 2023). Tourists often seek social support and empathy through online platforms when facing travel-related uncertainties, with such interactions shown to enhance their emotional states and travel intentions (Kim et al., 2020).

Couchsurfing, a leading P2P tourism platform, facilitates meaningful, noncommercial exchanges between travelers and local hosts, emphasizing social interaction over brand-driven engagement (Zgolli and Zaiem, 2018; Rafi et al., 2025). Unlike traditional online brand communities (P2P), it fosters social capital through trust and reciprocal relationships among members (Scaraboto and Figueiredo, 2022).

Prior studies identify two core dimensions of community interactivity structural and experiential as central to shaping user engagement and social relationships (Wiyata et al., 2025). Structural features encompass navigability, content accessibility and informational clarity, while experiential features involve emotional support, social bonding and relationship-building through online interactions (Chou et al., 2022). Both dimensions are theorized to influence social capital, particularly trust and reciprocity, which foster emotional well-being through mutual support and shared value exchanges (Lin et al., 2024).

Grounded in resource exchange theory, this study explores how structural and experiential features on Couchsurfing shape users’ emotional well-being through the mediating roles of social trust and reciprocity (Singh et al., 2023). The theory posits that emotionally supportive interactions fulfill intrinsic social needs, leading to improved emotional states (Meek et al., 2019a; Fleischer et al., 2022).

Accordingly, we pose the following research questions:

This study contributes to tourism marketing by exploring how emotional well-being is shaped within P2P platforms through trust and reciprocity. It applies resource exchange theory in a noncommercial context and combines structural equation modeling (SEM) with necessary condition analysis (NCA) to uncover both influential and essential pathways. By focusing on Couchsurfing, it offers fresh insights into the social dynamics that drive emotional outcomes in community-based tourism.

Interactivity in P2P tourism platforms has evolved beyond basic system usability to encompass user-driven social engagement, content co-creation and mutual responsiveness. Modern platforms enable users to navigate, respond and contribute in real time, fostering deeper emotional and informational exchanges (Cai et al., 2025). This shift toward interactive environments allows travelers to feel heard and valued, encouraging prolonged engagement and community formation (Stienmetz et al., 2022). Interactivity now includes multimedia tools, real-time messaging and participatory features such as peer reviews and experience sharing, all of which contribute to a richer user experience and platform loyalty (Lin et al., 2024).

Contemporary research emphasizes that interactivity in P2P tourism communities can be categorized into functional and relational dimensions. Functional interactivity involves accessible design, navigational ease and content relevance, which help reduce user anxiety and improve satisfaction (Chou et al., 2022). In contrast, relational interactivity centers on emotional support, community warmth and reciprocal communication critical for building trust and encouraging repeat participation (Prayag et al., 2023). These dual aspects are especially vital in platforms like Couchsurfing, where meaningful social exchanges not just information delivery create value (Kromidha et al., 2023). As platforms continue to embed interactive features tailored to both utility and connection, users are more likely to engage authentically and develop stronger ties with the digital tourism community (Garau-Vadell et al., 2023).

Resource exchange theory suggests that individuals engage in various exchanges – material, social or informational – to enhance their social functioning and effectiveness (Ahn et al., 2022). On P2P tourism platforms, such as Couchsurfing, users share destination knowledge and offer advice without expecting direct compensation (Chan and Li, 2010). These discretionary acts reflect the collaborative spirit of such communities.

Two key forms of participation – engagement duration and information sharing – serve as indicators of user involvement. While time spent online has long been used to measure engagement (Roy, 2009), more recent work emphasizes the emotional depth of these interactions, including the sense of belonging and personal meaning derived from social exchanges (Zhang et al., 2020; Wiyata et al., 2025). These emotionally engaging experiences often lead to stronger platform loyalty and word of mouth advocacy (Wang et al., 2023).

Beyond active contributors, even passive users benefit by accessing valuable community insights (Trivedi et al., 2022). However, it is the active participants who drive knowledge creation and mutual learning (Cheung and Lee, 2010), shaping tourist behavior through consistent and credible electronic word of mouth (Akinci and Aksoy, 2019). Community engagement not only influences travel decisions but also strengthens social bonds, particularly in densely connected networks where shared experiences enhance emotional well-being (Park et al., 2012; DiPietro et al., 2020). Ultimately, the quality and emotional tone of interactions play a central role in shaping user outcomes on P2P platforms.

Emotional well-being, often associated with satisfaction and psychological health, is increasingly recognized as a core outcome of platform interactivity. Interactive features contribute not only to information dissemination but also to the emotional states of users. Structurally, well-designed platforms offer clarity, consistency and reduced cognitive load, which in turn alleviate anxiety (Lin et al., 2024). More critically, experiential elements such as emotional support, perceived empathy and user recognition - create a sense of belonging and psychological safety (Wiyata et al., 2025). When users perceive the community as responsive and supportive, their emotional well-being is enhanced, reinforcing continued use and positive evaluations (Xue et al., 2021). Consequently, platform design must consider emotional cues and interactional warmth as key elements in user experience architecture (Baloglu et al., 2019).

The structural route reliably predicts user engagement; however, experiential routes, emphasizing social interaction, may have a greater impact, as highlighted by this study’s focus. Platforms fostering social connections encourage frequent content sharing (Prayag et al., 2023). Well-organized P2P platforms also facilitate reliable information access, reducing anxiety and enhancing satisfaction (Chou et al., 2022).

Platforms integrating structural and experiential elements promote interpersonal relationships and community support, helping users alleviate loneliness and enhance emotional well-being (Xiang and Qiao, 2023). Clearly defined norms encourage respectful interactions, creating an emotionally supportive environment, fostering happiness and emotional stability (Van Horn et al., 2001):

Emotional well-being refers to emotional quality of an individual’s every day experience, including the intensity/frequency of pleasant or unpleasant emotions (e.g. affection, joy, anxiety or anger) (Kahneman and Deaton, 2010). Emotional well-being involves a user’s emotional health and pleasure from consumption experiences, including interactions within tourism platforms. These interactions influence overall happiness, contentment and psychological well-being (Wang et al., 2021). Unlike traditional offline communities, P2P tourism platforms facilitate virtual interactions (Dessart et al., 2015).

Social trust and reciprocity within these platforms depend on user activities, content quality and social interactions (Meek et al., 2019a, 2019b). Social capital, comprising structural, cognitive and relational dimensions, enhances interactions (Meek et al., 2019a, 2019b). The structural dimension involves resource and knowledge exchange (Li et al., 2019; Zhang et al., 2020), while relational dimensions determine exchange quality (Muniz and O’Guinn, 2001).

Social trust (ST), encompassing goodwill, reliability and openness, emerges from continuous interactions among users (Nahapiet and Ghoshal, 1998). Trust encourages information sharing, fosters belonging and strengthens loyalty (Meek et al., 2019a, 2019b). Over time, deepened trust enhances platform interactions, fostering reliable community environments (Leung et al., 2020; Preece, 2001; Xue et al., 2021).

Reciprocity, defined as the expectation of mutual support, is crucial for maintaining interactions on platforms (Alalwan et al., 2019). Reciprocal exchanges enhance knowledge sharing and emotional support, improving subjective well-being (Meek et al., 2019a). Although both structural and experiential features may contribute to the development of social capital, this study differentiates their primary influence based on the nature of each dimension. Structural features (e.g. navigability, information richness) facilitate consistency and predictability in interactions, which are foundational to building social trust (Chan and Li, 2010). In contrast, experiential features (e.g. emotional support, shared experiences) are more interpersonal and emotionally driven, directly encouraging mutual exchanges and fostering reciprocity (Meek et al., 2019a). Therefore, while some overlap is theoretically possible, the current model focuses on the most salient pathways to maintain theoretical parsimony and reduce multicollinearity. These conceptual links guide the formulation of our mediation hypotheses involving social trust and reciprocity. Thus, hypotheses formulated are:

The theoretical frameworks (refer to Figure 1) provide a rigorous methodological foundation. While interactivity and resource exchange theories have been explored in various online settings (e.g. Chan and Li, 2010), limited research examines how these elements jointly influence emotional well-being within P2P tourism platforms such as Couchsurfing. Existing studies primarily concentrate on purchase behavior (Meek et al., 2019a) or brand loyalty (Kumar et al., 2021), neglecting psychological well-being outcomes derived from such interactions. Chan and Li (2010) highlight the significance of these pathways for user participation, whereas resource exchange theory clarifies how reciprocity and social trust mediate emotional well-being within these platforms.

The sample comprises local and international tourists who are active users of Couchsurfing, a global tourism and hospitality networking community connecting guests with hosts. This community has been conceptualized from a platform perspective, facilitating connections among tourists (Rafi et al., 2025). Several strategic factors influenced the selection of the Couchsurfing community for this study. First, Couchsurfing naturally promotes consumer-to-consumer communication exchanges, aligning with the primary focus of this study. Second, members of Couchsurfing provide a distinctive combination of informational and practical support, making the community particularly suitable for investigation.

Snowball sampling was employed for participant recruitment as a methodological choice. This approach enabled the identification and engagement of active, well-connected community members, resulting in the collection of rich and relevant data. This strategy served three distinct purposes: first, it facilitated the identification of a targeted group of Couchsurfing users who could form a valuable social support network for the research; second, it identified the most effective means of contacting these users; and third, it helped establish trust and rapport within the community. Snowball sampling was considered particularly appropriate for this study because it is effective in researching populations that are difficult to access using traditional sampling methods.

Identifying and recruiting Couchsurfing community members through random sampling or other probability-based methods is challenging, primarily due to the group’s specialized characteristics and wide geographic dispersion. Conversely, snowball sampling, leveraging existing social connections and networks, effectively reaches individuals otherwise difficult to access. These distinct advantages of snowball sampling align well with the goals of the present study, ensuring an appropriate sample composition.

Data were collected over a four-week period in September 2024 using a Google Form distributed via Couchsurfing networks. A total of 228 valid responses were obtained, achieving a robust response rate of 51%. As the authors are active participants in the Couchsurfing community, they utilized their connections to encourage other members to participate in the survey and share the survey link within their respective Couchsurfing networks, minimizing potential bias. This collaborative effort, coupled with the welcoming environment of the Couchsurfing community, significantly contributed to the high response rate.

Table 1 summarizes the demographic characteristics of the 228 respondents. Notably, 74% of respondents were men, with the largest age group (49%) between 18 and 23 years. The gender imbalance in the sample aligns with broader usage patterns on platforms like Couchsurfing, where men are typically more active. Concerns about safety and trust particularly in informal, host-based settings may discourage some women from participating, especially in the aftermath of COVID-19 when personal safety has become even more important in travel choices. Millennials comprised the majority (87%) of respondents. Furthermore, a substantial portion (69%) reported active engagement within the Couchsurfing community for five years, and 52% indicated using Couchsurfing services annually.

The survey questionnaire covered two primary sections: demographic information and factors related to the study. Specifically, the structural 4-items and experiential 3-items online community components were adopted from the framework developed by Chan and Li (2010). The social capital scale, including dimensions of social trust 3-items and reciprocity 4-items, was adapted from Meek et al. (2019a, 2019b). Emotional well-being was assessed using a comprehensive 10-item measure based on the paradigm proposed by Watson et al. (1988). The complete list of items utilized in this study is available in Appendix.

The study incorporates several procedural and statistical procedures to avoid Common Method Bias (CMB). For instance, procedural strategies included to mitigate CMB are that authors developed a comprehensive research information cover sheet. Second, ambiguous items were screened out so respondents could easily understand the items. Reverse coding techniques were employed to ensure a balanced representation of both positive and negative elements in the data. Utilizing Harman’s single-factor test was deemed more appropriate for its capacity to address a wide spectrum of critical issues, encompassing the identification of common method bias, comprehensive evaluation of method bias, discrimination of method effects and effective mitigation of common method bias, thereby enhancing the overall validity of the study.

The primary statistical methods utilized in the analytical framework encompassed Confirmatory Factor Analysis (CFA) and Harman’s single-factor analysis. Employing SPSS, factor analysis was conducted with the number of factors set as a fixed value of “1.” In this instance, the variance attributable to a single factor amounted to 36.419. Finally, all individuals’ Mahalanobis distances were confirmed to be lower than the necessary value for evaluating multivariate outliers, demonstrating the dataset’s appropriateness for analysis. After all requirements for SEM were satisfied, SEM was then used, made possible by Smart-PLS version 4.0, to clarify both the measurement and structural models encompassed inside the proposed research framework (Rather et al., 2024).

The evaluation of the measurement model is used to determine the quality of the study’s constructs. Evaluating the factor loadings is the first step in assessing the quality criteria, followed by determining the construct reliability and validity.

The degree to which each item in the correlation matrix connects with a specific principal component is called factor loading. Higher absolute values suggest a higher connection between the item and the underlying factor, with factor loadings ranging from −1.0 to +1.0 (Pett et al., 2003, p. 299). There were four items for emotional well-being and 1-item for social trust with lower factor loadings removed to have minimum criteria of 0.5 average variances extracted.

To evaluate multicollinearity in the indicators, the Variance Inflation Factor (VIF) statistic is used (Fornell and Bookstein, 1982). Multicollinearity is not a severe concern, per Hair et al. (2016), if the VIF value is less than 5. Table 2 shows the VIF values for the study’s indicators and demonstrates that each VIF is below the suggested level.

Smart-PLS 4.0 was used to evaluate concept validity and convergent reliability, as shown in Table 3. The results for Cronbach’s alpha, composite reliability and Average variance extracted (AVE) are presented in the Table 3. The Cronbach’s alpha ranged from 0.753–0.817, whereas composite reliability (CR) ranged from 0.856–0.889. Finally, convergent validity results, based on the current study’s AVE statistics, show that all the constructs meet the minimum criteria of 0.5 (Fornell and Larcker, 1981).

Discriminant validity, as defined in theory (Bagozzi et al., 1991), refers to the extent to which measurements of different concepts exhibit distinctiveness. Valid measures of distinct concepts should exhibit weak correlations. To establish discriminant validity, Fornell and Larcker (1981) criteria were applied, comparing the square root of a concept’s Average Variance Extracted (AVE) to its correlations with other constructs (as shown in Table 4). Meeting these criteria provides substantial evidence in support of establishing discriminant validity.

The evaluation of path coefficients and their associated statistical significance within the structural model occurs after the assessment of the measurement model. Hypothesis 1 (H1) seeks to determine whether the structural route exerts a significant positive influence on emotional well-being. As per the tabulated results, it is evident that the structural route has a substantial direct impact on emotional well-being through the mediating factor of social trust (Hypothesis 1: β: 0.142, t: 2.750, p < 0.001), thereby providing empirical support for H1. Similarly, Hypothesis 2 (H2) examines the extent to which the experiential route contributes to emotional well-being. The results in Table 5 and Figure 2 demonstrate a significant direct effect of the structural route on emotional well-being, mediated by social trust (Hypothesis 2: β: 0.414, t: 7.046, p < 0.001).

Table 6 lists model fit indices, including RMR, RMSEA, χ², NFI, CFI and TLI based on Albright and Park (2009) research. The NFI scored 0.941, indicating a good fit and reliability across different sample sizes, as noted by Fan et al. (1999). The RMSEA value of 0.045 suggests a good fit, with values below 0.08 considered good, 0.08–0.10 indicating a mediocre fit, and values above 0.10 denoting a poor fit. Model fit guidelines by Steiger (2007) recommend a RMSEA cutoff near 0.06. Overall, these indices suggest that the model fits the data well, with RMSEA, CFI, TLI and other indices within acceptable ranges.

An investigation into the putative mediating function of social trust in the relationship between the structural route and emotional well-being was conducted through mediation analysis. The findings, shown in Table 7, demonstrated an impressive indirect effect of the structural pathway on emotional well-being through social trust (Hypothesis 3:0.045, t: 2.621, p 0.001). While the mediator (social trust) was considered while analyzing the whole effect of the structure route on emotional well-being (β: 0.193, t: 3.659, p 0.001), it was found that the influence of the structural route on emotional well-being was diminished (β: 0.142, t: 2.750, p 0.001). This result supports Hypothesis 3 by highlighting the function of social trust as a complementary partial mediator in the link between the structural route and emotional well-being.

The findings also showed a substantial indirect influence of the experiential pathway on emotional well-being, which was mediated by reciprocity (Hypothesis 4:: 0.072, t: 1.398, p 0.001). These findings are shown in Table 7 of the results. It became clear that the experiencing route’s impact on emotional well-being was mitigated when the mediator (reciprocity) was introduced and the overall effect of the experiential route on emotional well-being was considered (β: 0.473, t: 7.825, p 0.001). These findings highlight reciprocity’s complementary partial mediation function in the relationship between the experiential route and emotional well-being, supporting Hypothesis 4.

A statistical technique called NCA is used to pinpoint elements or circumstances for a specific event or result. It seeks to establish the minimal set of circumstances that must exist for an event to occur. The foundation of NCA is the idea of necessity and sufficiency. A required condition must exist for a result to occur, but its mere existence does not ensure that the event will occur. In other words, if the prerequisite is not satisfied, the result cannot occur. An adequate condition, on the other hand, is one that, when true, ensures the result.

The effect size “d” and its accompanying statistical significance are used to determine whether a variable or construct is necessary. Effect size “d” is calculated by dividing the whole area that can produce observations, known as the scope, by the “empty” space, which is frequently referred to as the ceiling zone as shown in Table 8. Therefore, “d” covers the set of values between 0 and 1, particularly 0 ≤ d ≤ 1. Dul (2016) has proposed a classification system for determining the magnitude of ‘d’: values between 0 and d 0.1 are classified as indicative of a small effect, values between 0.1 and d 0.3 are indicative of a medium effect, values between 0.3 and d 0.5 are indicative of a large effect, and values between d 0.5 are indicative of a substantial effect, as defined by Richter et al. (2020).

PLS-SEM and NCA analyses both produce statistically significant findings. Elevations in the structural route and experiential route, which are exogenous constructions, typically correspond to increased levels of the outcome, which is emotional well-being as shown in the Table 8. However, it’s interesting to notice that the NCATable 9, emphasized to promote the manifestation of the outcome, emotional well-being, a particular threshold of the exogenous constructs (structural route and experiential route), must be met. The CE-FDH (Ceiling Envelopment-Free Disposal Hull) is a nonparametric method that draws a stepwise ceiling line to identify the maximum possible outcome given a condition, often resulting in a more liberal estimation of necessity. While CR-FDH (Ceiling Regression-Free Disposal Hull) is a conservative regression-based method that models the upper boundary of the data to estimate necessity more smoothly and reliably, reducing sensitivity to noise (Dul, 2016).

This study investigates the intricate relationships between tourists’ emotional well-being and the precursors of engagement within online communities, specifically focusing on two distinct pathways: structural and experiential routes. A brand community is a collection of social network connections where members interact with one another to build social capital (Horng and Wu, 2020). Social capital is one of the most popular theoretical frameworks for examining connections and social networks (Adler and Kwon, 2002). Social capital is a multifaceted structure, yet little research has been done on the interactions between these aspects in P2P, particularly cognitive ones.

According to studies, these cognitive aspects have been shown to predict relational dimensions (Van den Hooff and Huysman, 2009). However, the measures used in these investigations have a distinct meaning because they were carried out in a non-P2P setting. In contrast to Van den Hooff and Huysman (2009), who utilized social identity and trust as characteristics of relational social capital, Zhao et al. (2012) employed perceived similarity as cognitive social capital. However, the level of social trust and reciprocity within the community’s structure determines social capital in P2P context (Meek et al., 2019a, 2019b). The current study supports the idea that the relational aspects of ST and reciprocity norms may be positively influenced by the interactivity routes (structural and experiential). Therefore, research on the relationships between facets of social capital in the context of P2P can benefit from the current study’s findings.

This study contributes to theory by extending resource exchange theory into the emotional and relational dimensions of user experience within P2P tourism platforms. While prior research has focused on knowledge exchange (Wasko and Faraj, 2005), brand-related outcomes (Rubio and Marin, 2015) and community engagement (Morgan Thomas and Veloutsou, 2013), this study shifts the focus to emotional well-being as a critical outcome of social interactions. It shows that social trust and reciprocity – two core dimensions of social capital (Nahapiet and Ghoshal, 1998; Meek et al., 2019b) – mediate the relationship between community features and emotional outcomes in noncommercial tourism settings, such as Couchsurfing.

Rather than confirming transactional assumptions, the findings emphasize the limitations of rational models in explaining emotionally embedded behavior. In P2P settings, trust is not merely about expected returns (Cheung and Lee, 2010) but involves vulnerability, perceived safety and emotional recognition (Fleischer et al., 2022; Cai et al., 2025). Emotional well-being is also not reducible to utility gains but is deeply shaped by social connection, empathy and psychological safety (Baloglu et al., 2019; Wang et al., 2021). This reframing contributes to the literature by integrating emotional and social dimensions into the resource exchange framework, offering a more holistic model of user experience in digital communities.

This study also calls for theoretical expansion. Future research should explore the intersections of affect theory (Singh et al., 2023) and relational sociology to better understand how emotions, vulnerability and belonging operate in digital travel communities. Concepts such as emotional solidarity (Cai et al., 2025) and digital empathy (Chou et al., 2022) may help explain variations in well-being outcomes across user types and platform contexts. Finally, by combining SEM with NCA (Dul, 2016), this study contributes methodologically by identifying both sufficient and essential conditions – offering a stronger causal interpretation of emotional outcomes in tourism studies.

This study offers key insights for platform managers, policymakers and NGOs seeking to promote well-being and social innovation within the P2P tourism sector.

First, P2P platform managers must recognize that trust and reciprocity are central to emotional well-being. To ensure the sustainability of their communities and protect the quality of life of their members, they should focus on governance structures that support safe, transparent and inclusive interactions. This includes implementing robust identity verification, clearly outlining safety guidelines and actively engaging with a peer-reviewed feedback system.

Second, platform developers should prioritize designing spaces that actively foster a sense of belonging. Our findings indicate that experiential features, such as empathy, social bonding and emotional support, have a more significant impact on well-being than structural features. Therefore, managers should consider including shared storytelling forums, cultural exchange groups and facilitated online meetups in their platform design. These features enable members to build trust and share experiences before, during and after travel, thereby directly contributing to their psychological well-being and making the community more resilient.

Ultimately, policymakers and NGOs can capitalize on the social benefits of P2P tourism. Because platforms like Couchsurfing enable access to cultural exchange and mobility for people who might otherwise be excluded due to financial or social constraints, these stakeholders can promote public awareness through storytelling. By sharing positive experiences, they can reduce barriers to participation and enhance emotional well-being. Ultimately, policymakers and NGOs can view P2P tourism not just as an alternative form of hospitality but as a social innovation that promotes intercultural dialogue, reduces loneliness and fosters inclusive tourism.

The cross-sectional design limits the ability to infer causal relationships between platform engagement, social capital and emotional well-being. Future research could adopt longitudinal or diary-based approaches to capture emotional dynamics over time. While the study addresses cognitive and relational elements of social capital, structural dimensions such as network ties and embeddedness were not included. Incorporating these in future models may offer a more holistic view of social capital’s role.

Furthermore, snowball sampling, while effective for reaching active Couchsurfing users, constrains generalizability. Broader sampling techniques or mixed methods could help validate findings across different P2P platforms or cultural contexts. Future research could also examine moderating variables such as user personality, platform involvement or the length of community membership (Rather, 2021). Exploring how different types of social capital (bonding, bridging, linking) influence trust and emotional outcomes would enrich the theoretical scope. Finally, incorporating qualitative or ethnographic approaches could uncover deeper insights into the lived emotional experiences of P2P tourists and how trust and reciprocity manifest in real-life travel interactions.