Investigating the effect of service quality dimensions on travellers’ satisfaction with couchsurfing accommodation and subjective well-being in a sharing economy

Abstract

This study examines service quality dimensions that influence travellers’ satisfaction with peer-to-peer (P2P) accommodations and their subjective well-being in a sharing economy. Structured equation modelling was used to test the model based on an online survey of 183 couchsurfers with prior Couchsurfing experience. According to the findings, assurance and convenience significantly impacted travellers’ satisfaction with Couchsurfing accommodations. Furthermore, the findings revealed that couchsurfers had low expectations for tangibles, followed by adequacy service supply and understanding and caring regarding network lodgings. Besides, satisfaction with Couchsurfing accommodation positively influenced travellers’ subjective well-being, and satisfaction mediates the relationship between service quality and subjective well-being. Results showed that tangibles, adequacy service supply, and understanding and caring are not significant for couchsurfers because Couchsurfing focuses primarily on free hosting of couchsurfers and developing social networking between hosts and guests rather than providing amenities. Furthermore, the paper suggests that focusing on assurance and improving the Couchsurfing platform’s reviews and profiles system can increase trust among couchsurfers, contributing to a better travel experience.

Keywords:

• couchsurfing
• service quality
• satisfaction
• well-being
• peer-to-peer accommodation
• sharing economy

Introduction

The emergence of unique peer-to-peer (P2P) lodging platforms with different characteristics, such as sharing or renting a house, a bedroom, or a space, has contributed to the growth of the sharing economy in the hospitality industry (De Canio et al., 2020). In a sharing economy, Couchsurfing is more than simply another type of P2P hospitality; it is a rapidly growing alternative consumption style of an innovative network lodging (Zgolli & Zaiem, 2018). It has become increasingly popular among solo travellers whose primary objectives are to find free lodging, establish relationships with hosts, and exchange cultures (Chen, 2018). Its disruptive and creative business model has evolved to include novel features that have impacted the tourism and hospitality industries (Cho et al., 2022).

With the rise of Couchsurfing and other P2P lodging services like Airbnb and HomeExchange, the hotel industry faces new challenges in an already competitive economy (Kuhzady et al., 2022). Academics and professionals agree that service quality and satisfaction are essential to customers’ well-being (Shulga et al., 2021; Toni et al., 2021). In this line of reasoning, Kim and So (2022) argue that accommodation quality is a significant cognitive factor in a guest’s decision-making process and creates satisfaction and well-being. Similarly, Shin et al. (2021) assert that a guest’s evaluation of the service and the growth of satisfaction and well-being depend significantly on the quality of the accommodations. To increase guests’ satisfaction and well-being while competing in the dynamic hospitality business, managers must create a service model that can deliver a high-quality service experience (Toni et al., 2021). These strategies include providing high-quality services, amenities, and reasonable costs (Priporas et al., 2017a; Kandampully & Suhartanto, 2000).

The hotel and lodging industry now focuses more on guest experiences based on service quality than just product distribution due to the shift in guest experience (Aruan & Felicia, 2019). Similarly, it is frequently believed that improving lodging and service quality is essential to enhancing guests’ satisfaction (Saayman et al., 2018; Shin et al., 2021). However, guests’ satisfaction with the quality of service does not guarantee that they will return and use the service again or that it will improve their well-being (Priporas et al., 2017b). Potential factors include customers’ dissatisfaction with the surroundings, their desire to utilise and explore different accommodations, or the availability of other lodgings at a reduced or no price (Aruan & Felicia, 2019).

Couchsurfing, a sustainable lodging within the sharing economy, dominates the lodging industry for solo travellers because it provides free lodging as well as a homelike experience, a chance to socialise with locals, and an opportunity to learn about the culture (Uzunca & Borlenghi, 2019; Zgolli & Zaiem, 2018). These features distinguish Couchsurfing from other P2P accommodation platforms and motivate more travellers and hosts to join.

This study examines the relationships between service quality dimensions, satisfaction with Couchsurfing accommodation, and travellers’ well-being. Couchsurfing accommodation was used as a setting for study in nine East and Southeast Asian tourist destinations (Hong Kong, Beijing, Shanghai, Bangkok, Singapore, Tokyo, Seoul, Hanoi, and Kuala Lumpur). These destinations were chosen as a reference point for this study because they are popular tourist destinations among travellers worldwide (UNWTO, 2020). To the author’s knowledge, no study has looked into the interrelations between Couchsurfing service quality dimensions, traveller satisfaction, and well-being in P2P network lodging contexts.

Hence, compared to earlier studies in the lodging industry, this study contributes to the P2P accommodation and Couchsurfing literature as a travel accommodation alternative for solo travellers. Second, this is the first study to examine the concurrent and independent effects of service quality dimensions on satisfaction with Couchsurfing accommodations and their impact on travellers’ well-being. Previous studies suggested testing the validity and reliability of service quality dimensions across cultures and lodging contexts to generalise the findings further (Akbaba, 2006; Priporas et al., 2017b). As a result, Akbaba’s (2006) service quality model is tested in another accommodation type, such as Couchsurfing, in some of the most popular destinations for tourists in East and Southeast Asia. Finally, from a theoretical perspective, this study highlights travellers’ decision‐making process about network lodgings or P2P accommodation in a sharing economy. In practice, it provides significant insights for managers to understand travellers’ behaviour better and manage lodgings.

Theoretical framework and hypotheses

Network lodging and couchsurfing

The evolution of online social interactions has altered how people envision and conduct hospitality in the technology-based sharing economy, resulting in a new form of network lodging (Luo et al., 2022). Network lodging entails establishing a connection with people by contacting one another online before meeting in person and connecting offline (Zakaria et al., 2019). The experience of interacting and meeting people online and offline through P2P accommodation platforms (such as Couchsurfing, Airbnb, HomeExchange, and others) has changed the hospitality industry in today’s sharing economy (Uzunca & Borlenghi, 2019). Couchsurfing is a well-known example of network lodging in a sharing economy (Kuhzady et al., 2022).

Couchsurfing is a distinct social and economic model that enables Couchsurfers to connect using an online networking platform (couchsurfing.com) and then meet in person and further develop people-to-people relationships (Toni et al., 2021). Another critical aspect of Couchsurfing is that couchsurfers can write references and reviews and share their experience with Couchsurfing accommodation, which helps other couchsurfers choose their hosts and guests. Reputation and trust developed through these reviews and references are valuable among couchsurfers.

Couchsurfing was first initiated in 2003 to assist global travellers in finding temporary free lodging by connecting with available hosts online (couchsurfing.com), meeting in person, and allowing travellers to live with hosts for a few nights. Now with the growth of Couchsurfing, the platform has over 14 million members in over 200,000 cities worldwide who share their life and journey, turning travel into a truly social experience.

According to De Canio et al. (2020), travellers use network lodgings for the desire to socialise and the need to save money. With Couchsurfing, travellers stay and socialise with locals, have an ‘authentic’ homestay experience, and feel welcomed (Aruan & Felicia, 2019). Based on trust, Couchsurfing, a network lodging platform, provides its members with these amenities and social experiences for free (Hanchuk et al., 2020). Online trust is developed based on available information and interaction between the host and the guest, similar to offline trust (Decrop et al., 2018).

Service quality and satisfaction with couchsurfing accommodation

Service quality is determined by how well the customer’s needs are fulfilled and how well the service matches their expectations (Priporas et al., 2017a). The significance of service quality is well acknowledged in the lodging and hospitality industry (e.g., İçöz & Günay, 2021; Zakaria et al., 2019), and with the growing sharing economy, the provision of better service quality throughout the service encounter is critical for survival (Luo et al., 2022). Earlier studies measured service quality through various models based on Grönroos’s (1984) two-dimensional model of outcome and process. Similarly, Parasuraman et al. (1988) five-dimensional (i.e., tangibles, adequacy service supply, understanding and caring, assurance, and convenience) SERVQUAL model have been used to measure service quality. The SERVQUAL 5-dimensional model developed by Parasuraman et al. (1988) has been well-documented and adopted by researchers within the lodging industry (e.g., Akbaba, 2006; Priporas et al., 2017b; Zakaria et al., 2019). Akbaba’s (2006) five-dimension SERVQUAL model is the most useful when considering past studies analysing the service quality of hotel and lodging services.

Since the 1970s, scholars have focused on the complexity of measuring service quality, consumers’ expectations of the service, and their assessments based on the service experience (Uzunca & Borlenghi, 2019). Keeping in view the notion of expectancy-disconfirmation theory (EDT), "the psychological interpretation of an expectation-performance discrepancy" (Oliver, 2010: 22), the service quality dimensions are likely to affect travellers’ satisfaction "in terms of the performance of a product or service being better or worse than expected" (Oliver, 2010: 22).

As per the literature, this study contends that travellers’ satisfaction with Couchsurfing is based on the fulfilment of service quality dimensions (Akbaba, 2006). Based on EDT, in a P2P network service setting, the satisfaction of the customer is perceived to be an emotional exchange, and it can simply be achieved when a customer is certain about the fulfilment of their expectations from service encounters (Buhalis et al., 2020; Oh et al., 2022). The attribute-level approach to evaluating service quality can help determine how customers perceive service quality (cf. Albayrak & Caber, 2015). As a result, travellers may have a positive perception of one service quality dimension while having a negative perception of another of P2P network lodgings (Ahrholdt et al., 2017).

The relationship between service quality and satisfaction has remained one of the important research interests in the service quality area and has also been acknowledged in P2P accommodation settings (İçöz & Günay, 2021). In their study, Priporas et al. (2017b) reasoned that providing exceptional services to lodgers in a sharing economy is critical for developing a satisfying relationship between the service firm and the traveller. Likewise, Shin et al. (2021) and Kim and So (2022) concluded that service quality significantly affects consumer satisfaction. Besides, previous studies within the P2P accommodation context stressed the fact that the assessment of service quality is multidimensional and that the suggested dimensions (i.e., tangibles, adequacy service supply, understanding and caring, assurance, and convenience) cannot be standardised as they vary in different service settings and cultures (Akbaba, 2006; Priporas et al., 2017a; Zakaria et al., 2019).

Hence, in this study, the service quality of Couchsurfing accommodation is evaluated using Akbaba’s (2006) five dimensions (tangibles, adequacy service supply, understanding and caring, assurance, and convenience). The resultant five dimensions are explained: tangibles as ‘physical facilities, equipment, and appearance of facility’, adequacy service supply as ‘provision of service on time, hosts willingness to help and availability if needed’, understanding and caring as ‘flexibility in providing lodgings, provision of assistance, friendly behaviour, understanding guests, assurance as ‘instilling confidence in guests, safety and trust, knowledge of guests’, and convenience as ‘helping behaviour of hosts, accessibility, information and guidance’ (Zakaria et al., 2019). Based on the literature, the authors assume that the service quality dimensions will be critical in developing customer satisfaction with Couchsurfing accommodation. Hence, it is hypothesised that:

H1. In a P2P accommodation network, satisfaction with Couchsurfing accommodation is influenced by service quality dimensions: tangibles (H1a), adequacy service supply (H1b), understanding and caring (H1c), assurance (H1d), and convenience (H1e)

Satisfaction with couchsurfing accommodation and subjective well-being

Studies in the leisure and tourism industry have lately focused on the affective outcomes of customer experience, such as satisfaction, subjective well-being, travellers’ quality of life, and happiness (e.g., Huang et al., 2019; Lyu et al., 2018). Subjective well-being is based on the individuals’ assessment of their life as satisfactory (Filep, 2014). As a cognitive outcome, SWB has been adopted in tourism and hospitality and has been associated with customer experience being satisfied or unsatisfied within P2P accommodation settings that provide a new understanding of travellers’ behaviours after experiencing the services (Kim & So, 2022). Toni et al. (2021) related satisfaction with well-being in a P2P accommodation scenario in a sharing economy, explaining that service delivery creates experiences that promote satisfaction and significantly influence people’s well-being. Toni et al. expand on the notion of SWB, claiming that SWB seeks to understand what makes individuals happy and content. Previously, a study revealed that satisfying service experiences of visitors and tourists influence people’s quality of life and boost their SWB (Hwang & Lee, 2019).

In addition, İçöz and Günay (2021) emphasised that in a P2P accommodation scenario, the hospitality and lodging services must consider travellers’ satisfaction to grow their well-being. Even though the application and influence of satisfaction on SWB have been recognised in previous research, there is still a need to develop a deeper understanding of the satisfaction-SWB effect in the context of P2P accommodation such as Couchsurfing (Toni et al., 2021), which has been overlooked in prior studies.

Studies on the sharing economy and P2P lodging indicate that social interaction and self-development brought on by travel experiences enhance travellers’ satisfaction and overall well-being (Buhalis et al., 2020). Couchsurfing allows hosts and visitors to actively participate in sharing lodgings, socialising with one another, and learning from one another in ways that promote both their own and others’ well-being. Accordingly, satisfied travellers’ experiences with Couchsurfing accommodation are predicted to contribute even more to the growth of travellers’ well-being. Hence, it is hypothesised:

H2. Travellers’ satisfaction with Couchsurfing accommodation increases their subjective well-being

Mediating effect of satisfaction with couchsurfing accommodation

Activities involving leisure, travelling, and lodging can affect a traveller’s emotional state, intellectual, psychological, and physical aspects, which sequentially can persuade an individual’s general sense of well-being (Ito et al., 2017). Su et al. (2016) stated that an individual’s perception of service quality affects satisfaction and service experience. Moreover, the authors examined the relationship between satisfaction on individual well-being in the context of tourist destinations, and their results showed a positive mediating effect of satisfaction between service quality and subjective well-being. Previous studies inspected the positive mediating impact of satisfaction between service quality and quality of life perceptions or well-being (Shulga et al., 2021). Likewise, investigations within the tourism industry have focused on the social aspect of tourists’ quality of life and SWB (Filep, 2014; Toni et al., 2021). Other studies considered service quality, satisfaction, and SWB in various contexts. In prior research, Kim and So (2022) found that travellers’ satisfaction and well-being are highly impacted by their satisfaction with the quality of service provided by P2P accommodations.

Based on the above literature, current research in Couchsurfing, a network lodging, theorises that travellers’ satisfaction intermediates the relationship between service quality and subjective well-being. Travellers’ experience of quality service and satisfaction with the accommodation will give them a happier and more satisfying service experience. Hence, it is hypothesised that:

H3. Satisfaction with the Couchsurfing accommodation mediates the effect of service quality dimensions (tangibles (H3a), adequacy service supply (H3b), understanding and caring (H3c), assurance (H3d), and convenience (H3e)) on subjective well-being.

Based on the theoretical background and literature review, a conceptual model (see Figure 1) that depicts the interactions between different components has been developed.

Figure 1. Conceptual model. Source: Authors.

Methodology

Sample and procedure

This study adopted a self-administered survey methodology (online questionnaire) to collect data from the members of ‘Couchsurfing.com’. The study focused on verified solo travellers aged 18 and above who travelled to various tourist destinations in East and Southeast Asia (Hong Kong, Beijing, Shanghai, Bangkok, Singapore, Tokyo, Seoul, Hanoi, and Kuala Lumpur) and have prior experience with Couchsurfing. The target cities are well-known tourist attractions that attract travellers worldwide (Molz, 2013; World Tourism Organization, 2021). Moreover, Couchsurfing is one of Asia’s largest network lodging providers after Europe (Couchsurfing, 2019; Hanchuk et al., 2020). As a result, these criteria verify the sample’s appropriateness for testing the study’s proposed model. Figure 2 and Table 1 present the city-wise sample frame of respondents. Solo travellers were selected because solo travellers with low budgets prefer Couchsurfing, a P2P accommodation to cut down their accommodation costs, socialise with locals, cultural exchange, and explore local places with the help of hosts (Schuckert et al., 2018).

Figure 2. City-wise sample frame. Source: Authors.

Table 1. City-wise sample frame.

Destinations	Frequency	Percentage
Hong Kong	31	16.9
Beijing	17	9.3
Shanghai	23	12.6
Bangkok	39	21.3
Singapore	13	7.1
Tokyo	20	10.9
Seoul	19	10.4
Hanoi	11	6.0
Kuala Lumpur	10	5.5

Source: Authors.

The travellers were selected through a 2-stage sampling process. First, upcoming travellers in a city were searched through the ‘find travellers’ search option at Couchsurfing.com. Then, from the search results, ‘verified travellers’ were selected (the platform verifies the profiles by verifying a valid payment method, home address, government ID, or phone number of a Couchsurfing member). The reason to choose verified solo travellers is that hosts trust them more due to their verified information providing hosts with a sense of security about the guests they will host on their personal property. Further, travellers with their completed profile information were selected. Later, travellers with at least one reference and one Couchsurfing friend were selected. Furthermore, travellers with prior experience with Couchsurfing (i.e., more than or equal to 3 times usage of Couchsurfing) were filtered who also have references filled by the hosts they stayed with or guests they hosted.

Based on the above criteria, 300 respondents were selected to participate in the survey using a systematic random sampling method. Then, these solo travellers were contacted by authors individually through the option of ‘send message’ on members’ profiles and were asked to help in completing the survey questionnaire about their recent experience with Couchsurfing.

The authors concluded data collection over four weeks. At first, travellers were asked to take the online survey through the ‘send message’ option on the Couchsurfing member’s profile. A short research description and an online survey link were sent to 300 solo travellers based on their verified profiles. At the end of the first week, out of 300 travellers, 86 completed the survey. In the second week, a reminder was sent to the Couchsurfing members. At the end of the second week, 51 more members completed the survey, which led to 137 responses with a response rate of 45.66%. Second, in the third week of data collection, 150 Couchsurfing members were selected following the earlier procedure. At the end of the third week, 27 members completed the survey. In the fourth week of data collection, a reminder was sent to the members who did not complete the survey. As a result, 60 more members completed the survey by the end of the fourth week. Collectively, in the second phase, 87 out of 150 members completed the survey with a response of 58%. Altogether, this technique resulted in 224 responses out of 450 members contacted in the first and second phases of data collection, with a response rate of 49.78%.

After an initial review of the data, we removed 41 responses because the respondents didn’t answer all questions or the response was the same for all questions. Consequently, a final sample consists of 183 responses from solo travellers who used Couchsurfing accommodation. The sample size of 183 responses was considered sufficient to perform Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), which is above the absolute minimum sample size (Ekinci & Riley, 1998; Hair et al., 1998; Priporas et al., 2017b). The respondent’s demographic details are presented in Table 2.

Table 2. Demographic profile of the respondents.

Items	Category	Frequency	Percentage
Gender	Male	104	56.8
	Female	79	43.2
Age	18–22	37	20.2
	23–27	57	31.1
	28–32	49	26.8
	33–37	37	20.2
	38 and above	3	1.6
Education	Technical/Vocational	15	8.2
	Primary	21	11.5
	Bachelors	87	47.5
	Masters	51	27.9
	Doctorate	9	4.9
Income	<20,000	25	13.7
	20,000–39,000	60	32.8
	40,000–59,000	35	19.1
	60,000–79,000	32	17.5
	>80,000	31	16.9

Source: Authors.

Measures

Service quality was measured using 25 items categorised into five dimensions (tangibles, adequacy service supply, understanding and caring, assurance, and convenience) suggested by Akbaba (2006). Satisfaction with Couchsurfing accommodation comprised three items presented by Han et al. (2011). SWB was computed by three items adapted from the Subjective Happiness Scale (Lyubomirsky & Lepper, 1999). All measurement scales were used in previous studies that showed their validity in the hospitality industry, especially in network lodging or P2P accommodation studies. A 7-point Likert scale (1 = strongly disagree and 7 = strongly agree) was utilised to measure all items. A pilot study was conducted among 20 graduate students. The average time to finish the research survey was 15 min. Responses from the pilot study helped in the improvement of the questionnaire and to make it simple for the respondents to answer the questions.

Results

Statistical approach

The proposed model with hypothesised relationships was tested using Structural Equation Modeling (SEM) technique with principal components in AMOS 23. A two-stage process was used to access the measurement and structural models. As an effective instrument to execute these tests, the SEM technique (Anderson & Gerbing, 1988) was performed in this study because it allows for conducting a simultaneous analysis of a complete arrangement of variables in a theorised model (Byrne, 1994).

Assessment of bias

A self-administered survey questionnaire including dependent and independent variables was used to collect data that might have raised the concern of common method bias, which could generate biased results. Therefore, we analysed data with Harman’s single-factor test to assess this potential concern of common method bias (Harman, 1976). Harman’s single-factor test revealed that the initial factor explained only 42.548% of the variance. Hence, the results indicate that data does not account for the potential effects of common method bias.

Measurement model analysis

Scale validity in the study was measured through confirmatory factor analysis (CFA). Benchmark values for factor loadings, composite reliability (CR), and average variance extracted (AVE) are 0.7, 0.7, and 0.5, respectively (Fornell & Larcker, 1981). The analysis results in Table 3 show that all factor loading range between .801 and .995, Cronbach’s alpha between .924 and .988, CR between .85 and .96, and AVE values range between .58 and .84. Thus, the findings satisfy the accuracy of measurement model (Fornell & Larcker, 1981). However, the final analysis excluded one item for tangibles and two for adequacy service supply due to lower factor loadings.

Table 3. Reliability and confirmatory analysis.

Items	Mean (SD)	Loadings	α	CR	AVE
Tangibles
TAN1 Adequate capacity	4.64 (1.49)	.933	.980	.96	.81
TAN2 Modern-looking equipment	4.63 (1.43)	.954
TAN3 The equipment of the lodging works properly	4.63 (1.50)	.945
TAN4 Materials associated with the services are adequate and sufficient	4.54 (1.49)	.976
TAN5 Atmosphere and equipment comfortable and appropriate	4.60 (1.50)	.944
Adequacy service supply
ASS1 Providing the services as they were promised	4.95 (1.53)	.979	.988	.96	.84
ASS2 Performing the services right the first time	4.93 (1.54)	.976
ASS3 Couchsurfing owners are always willing to serve	4.96 (1.51)	.995
ASS4 Couchsurfing owners are always available when needed	4.90 (1.46)	.930
ASS5 Provision of services at promised times	4.88 (1.58)	.960
Understanding and caring
UC1 Flexibility in services	4.39 (1.53)	.994	.966	.95	.78
UC2 Providing assistance in other required areas	4.50 (1.58)	.903
UC3 Treating guests in a friendly manner	4.40 (1.64)	.879
UC4 Understanding the specific needs of guests	4.46 (1.61)	.944
UC5 Individualised attention	4.34 (1.60)	.805
Assurance
AS1 Convenient operating hours	5.10 (1.33)	.961	.950	.85	.58
AS2 Providing a safe and secure place	5.16 (1.31)	.928
AS3 Instilling confidence in guests	5.13 (1.40)	.801
AS4 Occupational knowledge of Couchsurfing owners	5.20 (1.33)	.824
Convenience
CON1 Resolving guest complaints	5.31 (.96)	.901	.924	.92	.79
CON2 Ease of access to the lodging	5.36 (.96)	.913
CON3 Reaching information	5.33 (1.0)	.865
Satisfaction
CS 1 I am happy with my decision to stay at Couchsurfing accommodation	5.20 (1.37)	.951	.958	.91	.77
CS2 I believe I did the right thing when I stayed at Couchsurfing accommodation	5.11 (1.44)	.948
CS3 Overall, I am satisfied with the decision to stay at the Couchsurfing accommodation	5.12 (1.43)	.894
Subjective well-being
SWB1 In general, I consider myself a very happy person	5.44 (1.37)	.888	.929	.89	.73
SWB2 Compared to most of my peers, I consider myself happier	5.48 (1.31)	.898
SWB3 I am generally very happy and enjoy life	5.50 (1.28)	.911

Source: Authors.

Additionally, discriminant validity explains "the level of the construct and its indicators to be different from other constructs and their respective indicators" (Leong et al., 2015: 6627). In Table 4, the value of the square root of AVE presented in the diagonal cell was greater than the correlation between the related constructs. This test indicates that data satisfies the discriminant validity (Fornell & Larcker, 1981).

Table 4. Discriminant validity: correlation coefficients.

Constructs	TAN	ASS	UC	AS	CON	SAT	SWB
Tangibles	1
Adequacy service supply	.439**	1
Understanding and caring	.437**	.383**	1
Assurance	.454**	.536**	.450**	1
Convenience	.140	.182*	.061	.426**	1
Satisfaction	.294**	.247**	.326**	.522**	.362**	1
Subjective well-being	.294**	.365**	.292**	.541**	.381**	.439**	1

Note: **Correlation is significant at the 0.01 level, *Correlation is significant at the 0.05 level.

Source: Authors.

Moreover, the model fits were assessed by four goodness-of-fit measures; the normed fit index (NFI), comparative fit index (CFI), and the root mean square error of approximation (RMSEA). Established on Byrne (1998) propositions, a model is acceptable if CFI exceeds .90, NFI exceeds .90, and RMSEA is less than .08. As per CFA analysis, overall measurement model fitness indices were satisfactory (χ²/df = 1.76, RMSEA = .06, CFI = .97, NFI = .92) as the values surpassed the suggested thresholds (Arbuckle, 2003) as illustrated in Table 5.

Table 5. Measures of the model fit.

Goodness of fit measures	χ^2/df	RMSEA	CFI	NFI
Recommended value	≤3.00a	≤0.08b	≥0.90a	≥0.90a
CFA model	1.76	.06	.97	.92
Structural model	1.85	.07	.96	.92

Note: CFI = Comparative Fit Index; NFI = Normed Fit Index; RMSEA = Root Mean Square Error of Approximation.

Source: Authors.

Structural model analysis

Resembling the measurement model, four goodness-of-fit measures were employed to measure the goodness-of-fit of the structural model. As mentioned in Table 5, structural path model results regarding the fitting indices (χ²/df = 1.85, RMSEA = .07, CFI = .96 and NFI = .92) of the proposed model are acceptable in comparison to the benchmark values (Arbuckle, 2003; Hair et al., 1998). So, it is suitable to evaluate the hypothesised paths.

Hypothesis testing

The path analysis conducted in the study is explained by the significance of a path established on its p-value. Concerning service quality dimensions, hypothesis results (see Table 6) disclose that H1a, H1b, and H1c were rejected. In sample analysis, tangibles (β = .063, p > .05), adequacy service supply (β = −0.08, p > .05) and understanding and caring (β = .094, p > .05) showed no significant impact on satisfaction. However, assurance predicted the most towards satisfaction (β = .447, p < .001), followed by convenience (β = .273, p < .01), resulting in a significant and positive impact on satisfaction. Hence, H1d and H1e were supported. Moreover, satisfaction showed a positive and significant effect on subjective well-being (β = .453, p < .001), confirming H2.

Table 6. Results of hypotheses testing.

Hypothesis	Paths	Path coefficient (β)	S.E	ULCI	LLCI	Remarks
Main effect
H1a	TAN → SAT	.063 ns	.071	–	–	Not Supported
H1b	ASS → SAT	−0.08 ns	.101	–	–	Not Supported
H1c	UC → SAT	.094 ns	.074	–	–	Not Supported
H1d	AS → SAT	.447**	.069	–	–	Supported
H1e	CON → SAT	.273**	.107	–	–	Supported
H2	SAT → SWB	.453***	.069	–	–	Supported
Mediation effect
H3a	TAN → SAT → SWB	.099	.037	.04	.181	Supported
H3b	ASS → SAT → SWB	.076	.034	.018	.150	Supported
H3c	UC → SAT → SWB	.132	.046	.053	.235	Supported
H3d	AS → SAT → SWB	.112	.052	.013	.217	Supported
H3e	CON → SAT → SWB	.171	.052	.076	.283	Supported

Note: TAN = Tangibles; ASS = Adequacy service supply; UC = Understanding and caring; AS = Assurance; CON = Convenience; SAT = Satisfaction; SWB = Subjective well-being; *p < .05; **p < .01; and ***p < .001; Bootstrap sample size = 5,000; ULCI = upper limit at 95% confidence intervals; CILL = lower limit at 95% confidence intervals.

Source: Authors.

Finally, to test the mediation hypothesis (H3), this study employed a bootstrapping technique to investigate mediation effects (Preacher et al., 2007). We used a bootstrap sample size 5000 for indirect relationships to create asymmetric confidence intervals (CIs). Table 6 exhibits the indirect effects of service quality dimensions on subjective well-being. All the effects are significant at 95% confidence level; H3a (β = .099; 95% CI = [.040, .181]), H3b (β = .076; 95% CI = [.018, .150]), H3c, (β = .132; 95% CI = [.053, .235]), H3d (β = .112; 95% CI = [.013, .217]), and H3e (β = .171; 95% CI = [.076, .283]). The findings support H3.

Discussion and conclusion

This study investigated the relationship between service quality dimensions (tangibles, adequacy service supply, understanding and caring, assurance, and convenience) and travellers’ satisfaction with Couchsurfing accommodations and how that relationship affected their subjective well-being. The current study adds to the knowledge of service quality, satisfaction, and well-being, providing insights for future research and practice.

First, when comparing Couchsurfing accommodations to other lodgings, Akbaba (2006) service quality dimensions exhibited contrasting results (e.g., Priporas et al., 2017b). Two service quality dimensions, assurance (β =.447) and convenience (β =.273) led to increased satisfaction with Couchsurfing accommodations, supporting H1d and H1e. These two dimensions reflect previous research findings in the lodging sector that also apply to Couchsurfing lodgings (Akbaba, 2006; Priporas et al., 2017b), demonstrating that they are essential determinants in determining service quality in Couchsurfing accommodations, supporting an earlier study by Molz (2012).

The results revealed that tangibles, adequacy service supply, and understanding and caring do not significantly affect travellers’ satisfaction with Couchsurfing accommodations, supporting H1a, H1b, and H1c. Authors assert that the service dimensions that are more important in other lodgings and service settings, such as Airbnb, HomeExchange, or traditional hotels, may not be as essential or desirable for couchsurfers (Aruan & Felicia, 2019; Kuhzady et al., 2022; Priporas et al., 2017b). Couchsurfers’ primary purpose is to stay a night or two at a host’s personal property for free (Chen, 2018), and they also plan to explore local places, socialise with hosts, and share their culture, language, and food. Furthermore, as an alternative form of hospitality, Couchsurfing focuses on shared experience over luxuries (Molz, 2012).

The results support H2 by demonstrating that traveller satisfaction has a strong influence on SWB (β =.453). The results confirmed earlier studies highlighting SWB's uniqueness in travel and lodging research (Saayman et al., 2018; Su et al., 2016). It is important to note that the findings of a network lodgings study on the strong association between satisfaction and SWB reveal and likely underline the need to consider emotional variables when assessing satisfaction and related traveller attitudes (Mahadevan, 2018). Because the P2P network business model, like in Couchsurfing, depends on developing an emotional connection between the host and the guest (Toni et al., 2021). As a result, P2P accommodation providers should focus on providing a positive experience that will eventually improve travellers’ well-being (Decrop et al., 2018).

The mediation test results demonstrate that service quality dimensions H3a (β =.099), H3b (β =.076), H3c (β =.132), H3d (β=.112), and H3e (β =.171) have a substantial effect on SWB through satisfaction. Results support H3 that satisfaction with Couchsurfing accommodation mediates between service quality dimensions and SWB (Hwang & Lee, 2019; Kim & So, 2022; Toni et al., 2021). Furthermore, the expectancy disconfirmation theory substantiates the quality-satisfaction-SWB model. It enhances the theoretical understanding that travellers’ satisfaction reflects overall assessments of various service quality dimensions and unique service characteristics (Aruan & Felicia, 2019; Oh et al., 2022). Although previous studies from the sharing economy perspective have tested the impact of service quality on satisfaction and loyalty behaviours (e.g., Priporas et al., 2017b; Zakaria et al., 2019), our study expands by considering the effect of service quality dimensions on the satisfaction of Couchsurfing accommodations and its impact on travellers’ SWB, which has been overlooked in P2P accommodation settings. Hence, Couchsurfing as a network lodging is demonstrated to be more than just another way of accommodation; instead, it is a fast-rising type of alternative consumption and experience in a sharing economy.

Managerial implications

This study provides some additional insights to service managers and platforms of network lodgings, especially for P2P accommodation services such as Couchsurfing, to improve their service offerings.

First, the study’s findings indicate that the Couchsurfing platform and hosts must pay attention to service quality dimensions and how they relate to satisfaction and SWB. The Couchsurfing business model, a unique and innovative lodging model, describes the relationship between quality-satisfaction-subjective well-being, linking the conventional service-dominant logic of hospitality with the innovative one of generating individual experiences of P2P lodging in a sharing economy (Yannopoulou, 2013).

The findings showed that, although Couchsurfing lodging is free, most hosts still think about providing assurance and convenience to their guests and seek to establish social connections that improve their Couchsurfing experience. Couchsurfing hosts are more able to comprehend how providing guests with a better experience may influence their subsequent behaviour, such as positive word-of-mouth, positive reviews, and referrals (Kamenidou et al., 2009; Su et al., 2016). Moreover, by investing in their platform’s service quality mechanism, which usually increases Couchsurfers’ satisfaction with the service platform, the Couchsurfing platform may enhance support for Couchsurfing services. Additionally, the review system on the Couchsurfing platform may be improved, increasing host and guest engagement in online communication and offline encounters.

Lastly, service managers need to realize how travellers who desire to experience alternate hospitality services perceive various service quality dimensions regarding P2P network lodgings. Moreover, managers must understand what factors affect travellers’ satisfaction with the accommodation and well-being and improve their services accordingly.

Limitations and future research

The study revealed some significant findings, but it still has limitations. First, the results of this study may not be generalisable because the study was limited to a few well-known Asian tourist destinations. This study revealed some notable findings, but it has some limitations. First, because the study was limited to a few famous Asian tourist destinations, the findings may not be generalisable. Couchsurfers in various areas may have different expectations of service. Therefore, the findings provide limited information regarding which service quality factors contribute to their satisfaction and well-being. Thus, future studies can study couchsurfers perceptions in different locations and may also include a comparison of Asian and Western cultures. Second, irrespective of the fitness of employing Akbaba’s (2006) measurement model and the study’s significant findings, future research may cross-validate the results by using alternative methods to test service quality, such as the lodging quality index and LODGQUAL. Third, based on the present paradigm of hospitality, future research may compare the lodger’s experience with Couchsurfing to that of other P2P accommodations, such as Airbnb and HomeExchange, to compare and generalise the findings. Fourth, further research can be performed using alternative methodological techniques, such as a mixed-method or qualitative approach, as this study was quantitative and has certain limitations surrounding survey-based data collection. Finally, the sample size in this study was smaller; the authors suggest using larger samples to increase the statistical significance of SEM.

Disclosure statement

No potential conflict of interest was reported by the authors.