1. Introduction
The development of emerging technologies such as the Internet and platform-based enterprises has given birth to the sharing economy, which has developed into a huge commercial economy in recent years. In the last decade, the sharing economy has developed rapidly around the world, reaching billions of dollars in scale and penetrating many industries, including accommodation, catering, transportation, and manufacturing. With the emergence of the sharing economy, shared tourism resources have significantly changed the way tourists travel, making sharing accommodation (SA) an important form of accommodation for tourists. SA uses a two-way transaction platform based on the Internet to match the SA need between hosts and tourists, meeting tourists’ non-standardized needs for accommodation and benefiting the platforms, hosts, and tourists in the sharing process [
1]. In recent years, SA has given full play to its platform advantages and become an important driving force for the digital transformation of the economy while meeting people’s daily accommodation needs.
The rapid development of SA has resulted in the accumulation of a large number of experienced users. The continuous use behaviors of existing users are important to maintain the sustainable development of SA. However, its rapid development has also brought serious problems and challenges such as information privacy leakage and personal safety injuries. For example, in May 2019, a guest of Airbnb in Qingdao was secretly photographed by the host, and the candid videos and photos were sold online [
2]. In March 2021, Urban Report reported that a couple was secretly photographed by the host for eight hours during their homestay, and the candid videos were also sold online [
3]. Worries on privacy leakage will affect users’ perceptions of the SA and their willingness to continuously use, which will ultimately jeopardize the healthy development of the industry. Therefore, how to promote the continuous participation of existing users under the condition of privacy concerns has become an important problem that urgently needs to be solved [
4]. This issue has also attracted great attention in the latest literature on SA.
Trust is considered to be one of the important factors to promote the continuous use intention of users [
5]. Trust helps to maintain a long-term connection between the trusting and the trusted. When transactions are opportunistic and uncertain, trust can promote risk-taking behavior [
6]. Existing research pointed out that in the platform-based economy, individual trust is not enough to facilitate user engagement behavior, and in such circumstances institution-based trust plays a more important role [
7,
8]. For example, Tussyadiah et al. [
5] pointed out that trust in the platform, as the institution-based trust, can significantly promote user participation in SA. Pavlou et al. [
7] believed that trust in the community of sellers, as a type of institution-based trust, can enhance users’ willingness to trade. In addition, some studies have emphasized the importance of trust in the user community to users’ continuous use intention [
9]. However, very few studies have comprehensively considered the transfer relationship of these institution-based trusts and their effects on continuous use intentions. Trust transfer, as an effective mechanism to build and enhance trust, has been explored in different research contexts [
10]. Based on prior research of institution-based trust [
7,
8], there are at least three types of institution-based trust in the context of SA in terms of the trusting objects (e.g., platform and users), named trust in the SA platform, trust in the host community and trust in the user community. According to Pavlou et al. [
7] and Lu et al. [
8], trust in the SA platform and trust in the host community are institution-based trusts [
7]. Similarly, trust in the user community, which represents a general opinion about the user community, is also a type of institution-based trust. In online context, users tend to rely on their peer users’ actions and recommendations [
11] to form their perceptions and judgments towards their transactional parties (e.g., platform or hosts). Thus, trust in the user community, as a type of perception towards the peer users, should help to engender trust towards the other two trusting objects, i.e., the platform and the host community. Drawing on trust transfer theory, this study proposes trust in the user community as a key antecedent of both trust in the platform and trust in the host community, and examines how trust is transferred from the user community to both the platform and the host community.
In addition, most studies ignore the boundary conditions under which trust transfer occurs. This will impede us to gain a deep understanding of how trusts are developed and take effect in the SA. Van der Heijden et al. [
12] also pointed out that when the trust reaches a certain level of evaluation, it no longer promotes people’s willingness to buy online. In recent years, scholars have called for further exploration of the boundary conditions where trust functions. Existing research mainly emphasizes the important role of institutional mechanisms as contextual variables for trust to be transferred and to take effect. For instance, Chen et al. [
13] explored the moderating effects of institutional effectiveness and perceived website quality on trust transfer. However, the institutional mechanism mainly considers the impact at the macro level, ignoring users’ situational awareness at the internal psychological level. Trust transfer is closely related to the risk context, and it does not occur independently of users’ inherent perception of risk, such as privacy concerns. Privacy concerns and trust are two negatively correlated constructs, but they are not antithetical. Individuals can perceive little trust and little privacy concern or have high trust but still perceive high privacy concern at the same time [
14]. This has given rise to the call to examine the moderation role of privacy concerns in online contexts [
15]. Despite the importance of privacy concerns, the literature rarely addresses its impact on trust transfer. This research gap is not helpful to gain an insightful understanding of whether and how trust transfer occurs in different risk scenarios in the context of SA.
Given the above research gap, this study first considers the transfer relationship among trust in the SA platform, trust in the host community, and trust in the user community based upon trust transfer theory. Second, this study applies and extends the privacy calculus model, taking privacy concerns as a contextual variable of trust transfer and exploring the extent to which it affects how trust in the SA platform and trust in the host community are transferred from trust in the user community. Finally, this study constructs a theoretical model including institution-based trusts, privacy concerns, and continuous use intention and employs empirical research methods to test this model. Through empirical testing, this study finds that trust in the user community positively affects trust in the SA platform and trust in the host community, trust in the SA platform and trust in the host community positively affect continuous use intention, and privacy concerns negatively moderate the impact of trust in the user community on trust in the SA platform and trust in the host community.
The main contributions of this study to related research are as follows: first, this paper comprehensively considers and studies the relationships of three types of institution-based trust in the SA and expands the research on trust transfer. Second, this paper reveals the effects of trust in the SA platform and trust in the host community on continuous use intention, which suggests the importance of institution-based trust on user behavioral intentions. Third, from the perspective of users, this paper examines the role of privacy concerns as a contextual variable of trust transfer and expands the research on the boundary conditions of trust transfer by revealing the moderating effect of privacy concerns in the SA. Fourth, this paper studies the interaction of trust and risk beliefs, thus extending the privacy calculus model by uncovering the moderating effect of privacy concerns on trust transfer.
6. Conclusions and Discussion
Based on previous research on institution-based trust and privacy concerns, this study reveals, firstly, the importance of three types of institution-based trust in the context of SA, namely, trust in the user community, trust in the SA platform and trust in the host community. Secondly, according to trust transfer theory, we propose that trust in the user community will positively affect both trust in the SA platform and trust in the host community. Thirdly, we explore the impacts of trust in the SA platform and trust in the host community on continuous use intention. Finally, this study takes privacy concerns as a contextual factor of trust transfer and uncovers the moderating effect of privacy concerns on the relationship between trust in the user community and trust in the SA platform, as well as the relationship between trust in the user community and trust in the host community. Through empirical research, this study has the following three major findings.
First, trust in the user community has a significant positive impact on both trust in the SA platform and trust in the host community. This finding discloses the relationships among the three types of institution-based trust in the SA from the perspective of trust transfer and confirms the importance of trust in the user community. In the SA, experienced users on the platform will provide their own opinions and evaluations based on their own experiences. Users’ beliefs in the peer user community should matter in the online context such as SA. Because the user community is generally associated with the platform (e.g., Airbnb) that users make transactions in and the host community that users have transactions with, trust can then be transferred from the user community to the other parties, i.e., the platform and the hosts, associated with the user community.
Second, trust in the SA platform and trust in the host community positively affect users’ continuous use intention. This finding is in line with the research of Mao et al. [
18], in which trust in the platform and the hosts are found to reduce the risk in the transaction process, thereby promoting transaction willingness. When users participate in the SA, they rarely transact with the same service providers. The interpersonal trust formed in user-seller interactions is thus ineffective in promoting continuous transaction willingness. Trust in the SA platform and trust in the host community, as institutional trust, then play a more important role in driving repeated transactions. This finding also confirms the importance of institution-based trust in the sharing economy [
7].
Third, privacy concerns weaken the relationship between trust in the user community and trust in the SA platform and the relationship between trust in the user community and trust in the host community. Drawing on the privacy calculus model, this study reveals the boundary condition under which trust is transferred. Different users hold different information privacy concerns when making SA transactions. Users with strong privacy concerns will generally seek other sources of trust or protective mechanisms to strengthen their trust toward both the platform and the hosts.
6.1. Research Implications
This research has three major theoretical contributions to the existing research. First, this study reveals the positive impacts of both trust in the SA platform and trust in the host community on continuous use intention, thus confirming the importance of institution-based trust in online contexts such as SA. Previous studies have emphasized and suggested the importance of institutional trust in the field of e-commerce. For example, McKnight et al. [
58] argued that in the absence of prior interactions such as e-commerce, institutional trust can enable unfamiliar members of society to cooperate and share with others. Based on our findings, this study finds that another type of institution-based trust, trust in the host community, can contribute to continuous use intention in addition to the effect of trust in the SA platform. Our study thus deepens the understanding of institutional trust by extending the institution-based trust to the SA context and illustrating the positive impact of trust in the host community on continuous use intention.
Second, this study expands the research on institution-based trust [
59,
60] based on the finding that trust in the user community is an important influencing factor for both trust in the SA platform and trust in the host community. Although the importance of institution-based trust has been demonstrated and tested in the sharing economy literature [
61], most of these studies focused only on trust in the SA platform, and trust in the host community and trust in the user community are two other types of institution-based trust that have received very little attention. In the SA context, we find that trust in the host community also has a positive and significant impact on users’ continuous use intention. At the same time, trust in the user community is an important source of both trust in the SA platform and trust in the host community. Therefore, this study comprehensively considers the three types of institution-based trust into one single model and examines the relationships among them, making a good complement to the existing research [
7,
62] on institutional trust.
Third, this research extends the research on trust transfer [
63] by examining the moderating effect of privacy concerns. Previous research [
13], mostly on the boundary conditions of trust transfer, has been conducted in the e-commerce context and most of them [
9] have only considered institutional factors as situational variables. The literature rarely examines the boundary condition of trust transfer from the individual user perspective. Users’ internal psychological state is also an influential situational factor when users participate in the sharing economy such as the SA. From the perspective of individual users, this study proposes privacy concerns as a situational factor under which trust is transferred and explores how privacy concerns affect the relationship between trust in the user community and trust in the SA platform and the relationship between trust in the user community and trust in the host community. Our study not only extends the research on privacy concerns and the privacy calculus model [
20] to the context of SA but also makes contributions to the existing research on trust and trust transfer [
18].
6.2. Practical Implications
First, the platform should pay attention to the important role of the user community and encourage them to offer their feedback, ratings, and comments concerning their past transactions. Trust in the user community is found to contribute to both trust in the SA platform and trust in the host community. Platforms should then find effective ways such as encouraging interactions among users and improving the effectiveness of user rating systems to enhance their trust toward the user community.
Second, for SA service providers and platform firms, our study finds that trust in the SA platform and trust in the host community can promote users’ continued willingness to participate. In SA, it is almost impossible for users to deal with the same host every time, so it is difficult to form interpersonal trust between individuals. Compared with interpersonal trust between individuals, institution-based trusts play more important role in promoting user behaviors. Platforms should then focus on building user trust from the institutional level. They should first enhance users’ trust in the SA platform by continuously investing in establishing effective institutional mechanisms (such as feedback mechanisms, escrow services, and provider certification) [
59], improving service quality, and building a good platform image. In addition, platforms can consider adding more trust-enhancing signals to their websites, such as hosts’ trust levels and rating scores, to offer more information to engender trust toward the host community.
Finally, our results show that the impacts of trust in the user community on both trust in the SA platform and trust in the host community are different under different conditions of users’ privacy concerns. Platforms should then give special attention to privacy concerns and their impacts in the context of SA. For users who are highly concerned about their privacy, the impact of trust in the user community on trust in the SA platform or on trust in the host community is weakened, as these users seek more assurance from other parties than the user community to handle their concerns about personal data. Platforms can alleviate users’ information privacy concerns by improving their compliance with the related laws and regulations and allowing authorities to monitor and supervise their practices and procedures regarding data collection, storage, processing and distribution. Platforms can also demonstrate their credibility by adopting relevant cutting-edge cyber security technologies, choosing reputable payment systems, and formulating privacy protection and compensation policies.
6.3. Limitations and Future Research Directions
This study still has some limitations. First, the survey data comes from experienced users of typical platforms in the SA industry, and the variables and meanings constructed may be different from users in other industries. Therefore, further testing is needed to generalize the results from a single industry to other sharing economy industries. Future research can further advance our investigation by including users in other industries, such as sharing mobility. Second, this study considers the moderating role of privacy concerns at the individual user level and does not consider the impact of other types of risk perceptions. Future research can then consider the impact of other risk perceptions on institution-based trust. Finally, with the survey method adopted in this paper, the respondents may be affected by the environment and other factors, which may cause deviations in the research results. In the future, various research methods can be considered to verify the measurement model.