Relational Benefits, Alternative Attractiveness and Customer Loyalty: Implication for Service Distribution Channels

Abstract

Purpose: This study explores the types of relational benefits that generate loyalty to room-sharing services among Chinese customers based on the relationship marketing literature. The study also examines the moderating effect of alternative attractiveness on this relationship. Research design, data and methodology: Based on research hypotheses, questionnaires with items measuring the proposed constructs in three dimensions, including relational benefits, alternative attractiveness, and customer loyalty, were designed to test the hypotheses. Data were collected via an online questionnaire of 220 room-sharing service customers in China. Results: Results verify the effects of relational benefits on customers' loyalty to room-sharing services and the mediating effect of alternative attractiveness. More specifically, confidence, social, and safety benefits positively affect customer loyalty to room-sharing services, and alternative attractiveness moderates only the effect of social benefits. Conclusions: The results suggest that room-sharing service providers should concentrate on providing confidence, social, and safety benefits to maintain long-term relationships with customers. This study also provides practical implication for building relationships between channel members in service distribution channels. The study concludes that without customer relationships marketing for managing collaborative and social communication channels, the entire distribution channel might lose out eventually.

1. Introduction

The “sharing economy” has experienced booming growth in recent years. Several kinds of businesses, including clothing (e.g., Rent the Runway), transportation (e.g., Uber, Lyft, and DiDi), and financial services (e.g., Prosper and Funding Circle), have been part of the rapid development of the sharing economy.

Recently, a sharing economy, known as room-sharing services, has emerged in the hospitality market. This new economic form is shaking up established categories and the traditional hospitality business worldwide. For instance, Airbnb, the most typical sharing-economy player in the hospitality industry, averages 425,000 guests per night and more than 155 million total guests per year, which is about 22% more than Hilton International averages (Price Waterhouse Coopers, 2015).

Following the growing success of Airbnb, the Chinese short-term hospitality market has also boomed in recent years, reaching 24.3 billion yuan in 2016. It is therefore important to understand why Chinese customers prefer to maintain certain relationships. Leading players in the short-term hospitality market include Tujia.com, Mayi.com, Xiaozhu.com, and Airbnb. However, previous research on the sharing economy has concentrated on Western rather than Asian countries, and few consider the Chinese context. Thus, it is meaningful to investigate room-sharing services rather than traditional room-purchasing service providers. This study attempts to answer this research question from the perspective of relational benefits to explain why a customer would choose to stay with a room-sharing service provider.

To date, three relational benefits related to customer satisfaction and loyalty have been identified: confidence, social, and special treatment benefits (Gwinner et al., 1998). However, in-depth explorations of relational benefits in specific service sectors, especially the room-sharing service sector, are scarce. Moreover, although relational benefits influence customer loyalty, there may be a moderating factor. Few studies have explicitly examined the conditions under which relational benefits may impact customer loyalty more strongly or weakly, but their impact may vary under different circumstances. Based on previous research showing that alternative attractiveness moderates the outcomes of service firms’ relationship efforts, the relationship between relational benefits and customer loyalty may depend on the degree of alternative attractiveness. For example, Jones et al. (2000) and Sharma and Patterson (2000) found that the effect of trust and satisfaction on commitment or loyalty depends on alternative attractiveness. Building on this background, the objectives of this study are twofold:

To examine the types of relational benefits that generate customer loyalty and explore the existence of additional relational benefits in the context of room-sharing services, especially in China.

To examine whether alternative attractiveness has a moderating effect on the relationship between customer loyalty and relational benefits.

The next section of this paper describes the theoretical background related to the sharing economy, relational benefits, alternative attractiveness, and customer loyalty and introduces a conceptual model with seven hypotheses. It then explains the research methodology, including the sample collection, scale of measurement, and analytical methods. The results are then presented. The final section describes the study’s contributions, implications, and limitations as well as opportunities for future work.

2. Literature Review

2.1. Sharing Economy and Room-Sharing Services

Although “sharing” is an old concept (Belk, 2014), the term “sharing economy,” first used by Professor Lawrence Lessig at Harvard Law School in 2008 and also known as the peer-to-peer or collaborative economy, refers to a contemporary phenomenon (Tussyadiah, 2016). This concept emerged in the past few years with the development of the internet (Belk, 2014) and was driven by economic and societal factors (Botsman & Rogers, 2010; Tussyadiah & Pesonen, 2016), technological advancements (i.e., smartphones), the global economic downturn that created a need for economic benefits (i.e., lower spending and cheaper prices for guests), the need for social connection, and a greater awareness of environmental issues (Botsman & Rogers, 2010; Gansky, 2010). It is defined as “the peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services” (Hamari et al., 2016). In the context of sharing-economy services, peers directly transact with the service and service providers provide their owned goods or resources through peer-to-peer business platforms to serve their customers. In addition, the sharing economy has unique features relative to its traditional counterpart. First, the objective of a transaction in the traditional economy is to transfer the ownership of a product, whereas the sharing economy is based on access to a product, meaning that people lend and borrow products or services rather than purchasing and owning them. Second, peer service providers are less likely to be industry specialists with professional training, and their shared services are more commonly offered for temporary and intermittent use rather than for business use. Third, as the meaning of sharing evolves, sharing behavior dissolves interpersonal boundaries (Belk, 2014). For instance, some Airbnb hosts do not initially intend to run a business but participate only “for the sake of shared enjoyment of whatever it is that is being shared” (Widlok, 2004), and they also treat guests as “family members.” Both of these notions differ significantly from traditional hospitality, which has clear interpersonal boundaries separating hotels and customers. In the hospitality market, room-sharing services are provided through such platforms as Airbnb and XiaoZhu (Wang & Nicolau, 2017). Locals share their extra rooms or other accommodations with travelers in exchange for a fee.

Most previous studies have explored other reasons that individuals participate in these services other than maintaining a relationship with a sharing service provider. For example, Kim et al. (2015) examine the intention to participate in sharing-economy services using the social exchange theory rather than investigating customers’ reasons for repurchasing a service of a sharing service provider. Moreover, some studies focus on the relationship between customers and sharing business platforms rather than on individual-level relationships. For instance, Lamberton and Rose (2012) identify the key drivers of customers’ choices of commercial sharing systems rather than investigating customers’ reasons of repurchasing a service of a sharing service provider at the individual level. In addition, research on sharing services in China is rather rare. Thus, studies examining Chinese customers’ reasons for staying in relationships with peer service providers in the context of sharing-economy services are lacking. This study fills these research gaps and helps room-sharing businesses in China develop marketing activities more effectively.

2.2. Customer Loyalty

Customer loyalty refers to a customer’s likelihood of making future repurchases or renewals from the current service provider (Yong-Ki Lee et al., 2008). Loyal customers help a service provider to promote its offerings through lip service and recommendations. They also increase the service provider’s profits by buying more products and services than non-loyal customers buy. Customer loyalty may be increased by a lack of real alternatives (Adreassen & Lindestad, 1998; Sharma & Patterson, 2000) and may also be increased directly or indirectly by relational benefits (Gwinner et al., 1998; Hennig-Thurau et al., 2002; Reynolds & Beatty, 1999). Thus, service providers should identify and understand how relational benefits and alternative attractiveness influence customer loyalty. The results of such analyses can enable service providers to build relationship marketing management to maintain their current customers and attract new customers.

2.3. Relational Benefits

Relational benefits refer to the benefits that customers receive beyond a company’s core offering and that are derived from an established, long-term relationship with a regular service provider (Gwinner et al., 1998; Reynolds & Beatty, 1999). In the relationship marketing literature, the relational benefits approach is a major theoretical framework for explaining why customers engage in relationships of exchange and maintain then over the long term (Kinard & Capella, 2006; Palmatier et al., 2006). Thus, this study uses relational benefits as the theoretical framework for explaining the mechanisms of customer loyalty in the context of room-sharing services. According to Gwinner et al. (1998), customers in long-term relationships receive three primary types of benefits: confidence benefits, social benefits, and special treatment benefits.

2.3.1. Confidence benefits

Confidence benefits are defined as feelings of trust or confidence in the provider along with a sense of reduced anxiety and comfort in knowing what to expect (Gwinner et al., 1998). Previous studies have reported positive relationships between confidence benefits and customer loyalty. Confidence benefits have been found to be the most important and the most commonly received benefits regardless of the service type (Gwinner et al., 1998), and their effect on loyalty primarily occurs through satisfaction (Hennig-Thurau et al., 2002). In the sharing economy, customers participate in services based on peer-to-peer interpersonal relationships and, thus, might be anxious about the quality of the services (Belk, 2014). Higher levels of confidence in their interactions with sharing-economy service providers will reduce customers’ anxiety regarding the provider’s ability to deliver the services, leading to a preference to continue the relationship (loyalty). Accordingly, the following hypothesis is proposed:

H1: Confidence benefits positively affect customer loyalty to room-sharing services.

2.3.2. Social benefits

Social benefits refer to customers’ perceived benefits from the emotional aspect of relationships (i.e. personal recognition, familiarity, and friendships) rather than from the outcomes of transactions (Gwinner et al., 1998). Previous studies have suggested a positive relationship between social benefits and customer loyalty (Goodwin, 1996; Goodwin & Gremler, 1996; Hennig-Thurau et al., 2002). For example, social benefits from established service relationships enhance customers’ social bonds with a service provider and improve the service experience (Bitner, 1995). However, in the sharing economy, customers may start and maintain social relationships for reasons beyond business purposes (Yang et al., 2017). For example, after an Airbnb experience, the host and the guest may become friends and may enjoy social benefits without further loyalty to the Airbnb business. Thus, social benefits may have no direct impact or a weaker impact on customer loyalty in sharing-economy businesses. Accordingly, the following hypothesis is proposed:

H2: Social benefits have no significant effect on customer loyalty to room-sharing services.

2.3.3. Special treatment benefits

Special treatment benefits mean that customers can receive faster services, monetary savings, or customized additional services, and they are the most tangible relational benefits (Fornell, 1992). Although Gwinner et al. (1998) and Ruiz-Molina et al. (2009) found that special treatment benefits positively influence customer loyalty, most researchers have suggested that special treatment benefits have an insignificant impact on behavioral outcomes (such as loyalty). For instance, Hennig-Thurau et al. (2002) find insignificant relationships between special treatment benefits and both customer satisfaction and customer loyalty. Molina et al. (2007) demonstrates that special treatment benefits are not important even if they are present in the retail banking industry. One argument for these results is that special treatment benefits are extrinsic rewards. They are likely to lead to temporary customer loyalty, but they do not contribute to the long-term relationships between service providers and customers. This insignificant effect of extrinsic rewards is referred to as “the hidden costs of rewards” (Frey, 1997).

In the sharing economy, many providers customize their services according to customers’ personal needs (Luchs et al., 2011). For example, Airbnb’s hosts offer such customized services as bicycles, movie nights, and home-cooked meals. This observation suggests that sharing-economy services have already been special in nature, implying that special treatments are not as “special” as they are in traditional business contexts. Because customers do not get additional special treatment benefits, such benefits have no impact on customer loyalty. Accordingly, the following hypothesis is proposed:

H3: Special treatment benefits have no significant effect on customer loyalty to room-sharing services.

This study reinvestigates three additional benefits in the context of room-sharing services: economic benefits, safety benefits, and epistemic benefits.

2.3.4. Economic benefits

The sharing economy is competitive in terms of economic benefits, as it provides lower costs to consumers. Sharing spaces with hosts creates benefits because consumers merely obtain access to resources rather than owning them (Hamari et al., 2016). Sharing a space rather than staying in a professionally furnished hotel room significantly reduces the cost of accommodations. In addition to costs saved on products, consumers can also save money on services. Whereas hotels hire teams of employees to deliver services to guests, person-to-person room-sharing services depend on individual hosts to carry out the entire service process. This cost-effective service model also directly reduces the cost of a stay for a consumer, who can rent a cheaper apartment or house during a trip (Stene, 2014). Thus, this study proposes economic benefits as a new type of relational benefit associated with room-sharing services. Accordingly, the following hypothesis is proposed:

H4: Economic benefits positively affect customer loyalty to room-sharing services.

2.3.5. Safety benefits

In many sharing-economy business models, concerns about user safety, privacy, and access are raised. According to a survey of consumers in the UK and the USA, safety is a major bottleneck for sharing-economy models. Unlike traditional companies, which are regulated and supervised, players in the sharing economy are usually unregistered. Thus, this study proposes safety benefits as a new type of relational benefit in the context of sharing-economy services. Here, safety benefits refer to the feelings of security that customers obtain from a service provider, with an emphasis on customers’ psychological relief regarding crime, such as the threat of danger, harm, or loss. Only a few prior studies have shown that safety, credibility, and security increase trust in a supplier in the business-to-business marketing context (Leung et al., 2005). Other recent business-to-consumer studies have discussed patients’ safety expectations in the context of health-care services (Engström & Elg, 2015). Hence, studies of the relationship between safety benefits and customer loyalty from the perspective of relationship marketing are lacking. Based on the rationale that safety reduces a customer’s psychological costs (Grönroos, 1997), once a customer has a sharing experience with a peer provider with no crime issues, the customer will expend less cognitive effort worrying about whether the service provider will create risks to personal safety, thus enhancing loyalty to the service provider. Accordingly, the following hypothesis is proposed:

H5: Safety benefits positively affect customer loyalty to room-sharing services.

2.3.6. Epistemic benefits

This study also proposes epistemic benefits as an additional relational benefit in the context of room-sharing services. Epistemic benefits refer to the benefits acquired from a product’s capacity to satisfy curiosity, provide novelty, and meet a user’s desire for knowledge (Sweeney & Soutar, 2001). Exploratory, novelty-seeking, and variety-seeking consumption behavior are examples of the pursuit of epistemic value (Kim et al., 2015). When customers receive epistemic benefits from one service provider, they may switch to other providers to fulfill their desire for new experiences. For example, Airbnb guests may receive customized services and have a chance to discover the local culture by staying and interacting with a host. Then, they may choose a different host to obtain different services or experiences. Thus, epistemic benefits may be positively related to relationship intentions but may have no effect on relationship retention in the case of room-sharing service providers. Accordingly, the following hypothesis is proposed:

H6: Epistemic benefits have no significant effect on customer loyalty to room-sharing services.

2.4. Alternative Attractiveness

In competitive environments, the number of alternatives in the marketplace increases based on the principal of demand and supply. Thus, consumers may choose products or services that fulfill their needs and personal preferences. In a competitive market, the possibility of emerging alternatives is high, and, thus, the possibility that a customer will replace his or her current service provider is high. Alternative attractiveness is defined as customers’ perceptions regarding the extent to which viable competing alternatives are available in the marketplace (Jones et al., 2000), and it influences consumers’ decisions to stay with their current service providers (Colgate & Lang, 2001) or to switch to other rivals with more attractive offers (Saidin et al., 2018). Ping (1993) proposed that when feasible competing alternatives are lacking, the likelihood of terminating a current relationship with a service provider decreases. Feather (1995) found that the valences of alternatives influence the choices of alternatives. In other words, if a customer perceives an offering’s valence, that is, if one is aware of the benefits from the relationship with a service provider, he or she is likely to continue the relationship with the current service provider. According to Jones et al. (2000), when alternative attractiveness is high, the repurchase intentions for alternatives are high. Thus, relational benefits have a large impact in this context. In other words, if a customer still receives relatively greater benefits from the current service provider than from alternative providers, he or she is likely to repurchase the current service. Accordingly, the following hypothesis is proposed:

H7: Alternative attractiveness moderates the effect of relational benefits on customer loyalty to room-sharing services. The effect of relational benefits on customer loyalty is higher when alternative attractiveness is high than when it is low.

3. Research Methods and Materials

3.1. Research Model

This study forms the basis for a conceptual model of the determinants (relational benefits) of customer loyalty to room-sharing services and a moderator (alternative attractiveness) of these relationships, as shown in Figure 1. In addition, as socio-demographic characteristics also influence behaviors (Panzone et al., 2016), gender, educational level, platform, and travel type are added to the proposed model as control variables.

Figure 1: Conceptual model of the determinants of customer loyalty to room-sharing services and a moderator

3.2. Sample and Data Collection

The data were collected through an online questionnaire for Chinese participants who had previously used a room-sharing service.

The questionnaire was sent via Wechat and remained open for one week, providing a final sample of 220 subjects. According to the 2016 China Room-sharing Service Markets Development Report from the China Industry Research Institute, 60% of active users of room-sharing services in China are ages 20-30. Thus, the sample only includes respondents ages 20-30. A frequency analysis of the demographic data was conducted using Statistical Package for the Social Sciences (SPSS). As Table 1 shows, most respondents are male (52%), have at least college degree (84.5%), use Airbnb (42.5%), and most frequently use room-sharing services for leisure travel (86.5%).

Table 1: Respondent demographics​​​​​​​

3.3. Measurement

Questionnaires with items measuring the proposed constructs in three dimensions, including relational benefits, alternative attractiveness, and customer loyalty, was designed to test the hypotheses. All constructs and items were adapted from previous studies and were measured using a five-point Likert scale (i.e., 1: strongly disagree to 5: strongly agree). As the target group is Chinese consumers, the questionnaire was written in Chinese. The measurement items and the scales of all the constructs are designed as shown in Table 2.

Table 2: Measurement items and scales​​​​​​​

4. Results

4.1. Validity and Reliability Test

Using a validity and reliability test in SPSS, the dimensionality and internal consistency of the constructs is assessed. First, as a validity test, a confirmatory factor analysis is employed to evaluate measures developed by the previous studies. Principle component analysis is separately conducted for each construct except economic benefits, as it only has one item. Two measures are used to assess the appropriateness of factor analysis. The Kaiser-Meyer-Olkin measures of sampling adequacy are 0.751, 0.755, 0.749, 0.500, 0.500, 0.741, and 0.500, all of which exceed the acceptable level of 0.500. Additionally, Bartlett’s test of sphericity (significant at p = .000) shows significant correlation among the variables. Thus, conducting factor analysis is appropriate.

Second, a reliability test is conducted for all factors to estimate the reliability of each scale. According to Tussyadiah (2015), all factors with Cronbach’s alpha values above 0.8 should be considered acceptable. Table 3 presents the results of the factor analysis and the reliability test. The factor loadings of all items are larger than 0.80, and the eigenvalues are larger than one. Cronbach’s alpha is larger than 0.80 for six of the constructs and is nearly 0.80 for the customer loyalty factor (Cronbach’s alpha = 0.794). These results indicate that the scales have validity and reliability and, thus, are acceptable for the subsequent analysis.

Table 3: Factor analysis and reliability test results​​​​​​​

4.2. Multiple regression analysis

Descriptive statistics and correlation analysis results are presented in Table 4. Multiple regression analysis is adopted to test the hypotheses, and the results are shown in Table 5. Multiple regression analysis is adopted to test the hypotheses, and the results are shown in Table 5.

Table 4: Descriptive statistics and Pearson correlation coefficients

Note: CB(Confidence Benefits); SOB(Social Benefits); STB(Special Treatment Benefits); ECB(Economic Benefits); SAB(Safety Benefits); EPB(Epistemic Benefits); ALT(Alternative Attractiveness)

*** p<0.01, ** p<0.05, * p<0.1

Table 5: Multiple regression analysis results

Note: CB(Confidence Benefits); SOB(Social Benefits); STB(Special Treatment Benefits); ECB(Economic Benefits); SAB(Safety Benefits); EPB(Epistemic Benefits); ALT(Alternative Attractiveness)

*** p<0.01, ** p<0.05, * p<0.1

Model 1 examines the effects of relational benefits on customer loyalty to room-sharing services. As the standard regression coefficients of confidence (beta = .573, t-value = 7.817, p < .01), social (beta =.138, t-value = 1.750, p < .10), and safety benefits (beta = .131, t-value = 1.882, p < .10) are significant and positive, all three benefits positively affect customer loyalty to room-sharing services. Moreover, as the standard beta of confidence benefits (std. beta = .551) is larger than those of social (std. beta = .145) and safety benefits (std. beta = .138), the influence of confidence on customer loyalty is most important. However, the standard regression coefficients of special treatment, economic, and epistemic benefits are insignificant. Thus, H1, H3, H5, and H6 are supported, and H2 and H4 are rejected. Model 2 tests the moderating effect of alternative attractiveness on the relationship between relational benefits and customer loyalty. The standard regression coefficient of the interaction term SOB * ALT (beta = .213, t-value = 2.873, p < .01) is significant. Additionally, the F-value associated with R2 changes by 40.817. However, the standard regression coefficients of the other interaction terms are insignificant. Thus, alternative attractiveness only moderates the effect of social benefits on customer loyalty to room-sharing services. This effect is strengthened when alternative attractiveness is high. Thus, H7 is partially supported.

In model 3, the demographic characteristics of gender, education, platform, and type of travel are transformed into dummy variables to test their effects on customer loyalty. The standard regression coefficients of SOB (beta = -.568, t-value = -2.104, p < .0), ALT (beta = -.639, t-value = - 5.185, p < .01), and the interaction term SOB * ALT (beta = .205, t-value = 2.723, p < .01) are similar to those found by model 2. Moreover, the F-value associated with R2 only changes by 13.984. Thus, including demographic characteristics as control variables makes no difference in the estimated relationship between relational benefits and customer loyalty.

5. Discussion and Conclusions

5.1. Managerial implications

The analysis results show the effects of relational benefits on Chinese customers’ loyalty to room-sharing services and the mediating effect of alternative attractiveness. More specifically, confidence, social, and safety benefits positively affect customer loyalty to room-sharing services, and alternative attractiveness moderates only the effect of social benefits.

These results of this study indicate that special treatment, economic, and epistemic benefits have no significant effect on customer loyalty to room-sharing services. This result suggests that providers’ efforts in offering special treatment (e.g., free bicycles, movie nights, or home-cooked meals), economic (e.g., guests who check in before June receive a 20% discount), or epistemic benefits (e.g., local culture experience projects) may attract new customers but may fail in maintaining current customers. Thus, room-sharing service providers should concentrate on providing confidence, social, and safety benefits to maintain long-term relationships with customers.

First, because this study shows that confidence benefits have the strongest effect on customer loyalty to room-sharing services, providers should make efforts to reduce customers’ anxiety regarding their service delivery skills. For instance, hosts can show that their services are highly recommended by professional travel magazines (e.g., Lonely Planet) or websites (e.g., TripAdvisor). Providers should also try to improve their online reviews and ratings (e.g., by providing coupons if guests give a good rating).

Second, because this study shows that alternative attractiveness moderates the effect of social benefits on customer loyalty to room-sharing services, providers should focus on fostering emotional bonds with customers to strengthen the impact of social benefits in competitive environments. Specifically, hosts may familiarize themselves with guests’ background information (e.g., names, ages, and hobbies) to generate positive conversations with guests and can act as travel guides to make guests feel as though they are being treated like family members.

Third, because this study also shows that safety benefits positively affect customer loyalty to room-sharing services, providers should act to reduce customers’ concerns about safety problems. For example, hosts should provide personal (e.g., photos, occupation, confirmation of verified identity card, and photo number) and room information (e.g., photos, videos, and facilities).

Finally, this study provides practical implication for building relationships between channel members in service distribution channels. Channel relationship management matters because the distribution channels link all manufacturers, wholesalers and retailers involved in providing and delivering goods until they reach end consumers. Especially, the service distribution linkage between service providers, their intermediaries, and customers requires each distributor to develop and maintain relationships with buyers. Thus, without customer relationships marketing for managing collaborative and social communication channels, the entire distribution channel may lose out eventually (Nevin, 1995; Weitz & Jap, 1995).

5.2. Theoretical Contribution

This study contributes to the literature on relationship marketing (Grönroos, 1997; Hennig-Thurau et al., 2002; Leung et al., 2005; Kinard & Capella, 2006; Palmatier et al., 2006; Gremler & Gwinner, 2015) and the new form of the sharing economy (Joo, 2017; Kim & Cho, 2018; Cho, 2020) by incorporating economic, safety, and epistemic enefits and the moderating effect of alternative attractiveness into the framework for testing the impact of relational benefits on customer loyalty to specific room-sharing services. The following concrete implications are provided. First, this study indicates that confidence benefits have a stronger effect on customer loyalty to room-sharing services than social and safety benefits have, which verifies the finding in previous research that confidence benefits are the most important and most often received benefits (Gwinner et al., 1998). Furthermore, different from the finding of Shuai Yang et al. (2017) that safety benefits have a very strong effect on customer loyalty in the sharing economy, this study shows that safety benefits have the weakest effect. This result may be explained by the fact that, although safety concerns exist in the hospitality industry (i.e., room-sharing services), the provider’s competence in service delivery is more important relative to other sharing-economy services (e.g., Uber in the transportation field).

Second, compared with the findings of Gwinner et al. (1998) and Ruiz-Molina et al. (2009) that special treatment benefits positively influence customer loyalty, this study shows that special treatment benefits have no effect on customer loyalty to a specific room-sharing service. This finding may arise because such treatment is not as “special” as it may be in traditional businesses because hosts always satisfy their customers’ personal needs (e.g., movie nights or free bicycles).

Third, this study shows that alternative attractiveness plays a moderating role in the relationship between social benefits and customer loyalty, which partially verifies the finding of Yong-Ki Lee et al. (2008) that alternative attractiveness acts as a homologized moderator in the relationship between confidence, social benefits, and customer loyalty. Specifically, even if customers face more choices among alternative service providers, if they perceive strong emotional bonds with their current provider (i.e., personal recognition, familiarity, and friendship), they tend to stay with that provider.

5.3. Limitations and future direction

This study has several limitations that provide opportunities for further research. First, because the sample only includes subjects aged 20-30, the results cannot be generalized to the overall population. Thus, future research can use a more comprehensive sample and incorporate other demographic characteristics (e.g., occupation and living days). Second, because this study was conducted in the Chinese context, cross-cultural research can be conducted to compare these results with those for Western countries. Third, future research can conduct a longitudinal study tracking relational benefits and customer loyalty over time. The effects may be specifically examined in the different stages of the relationships (e.g., started, processed, and terminated).