The sharing economy claims for research on its particularities and implications for management. This paper explores the way hosts of Peer-to-Peer Accommodation (P2P) develop relationship marketing with their guests and how it influences the business. The researchers conducted 30 semi-structured interviews to hosts of Airbnb, in order to obtain their perspective on the importance and application of relationship marketing in this context. Hosts with a B2C and a C2C business perspective were interviewed, and cultural differences in the relationship approach were also considered. The results show that the hosts are aware of the importance of interactions and personal contact with guests. Different results were identified depending on the type of business, accommodation, the culture and nationality of guests. Findings show that relationship marketing is highly explored in P2P sharing accommodation, exploring the interactivity of digital platforms to deepen those relationships.

“우버화”라는 용어는 비단 우버(Uber) 뿐만 아니라 에어비앤비(Airbnb) 등 과 같은 공유경제 산업이 활성화됨에 따라 운수업계, 숙박업계 등 기존 산업계와의 충돌로부터 빚어지는 현상을 의미한다. 혁신을 주도하는 새로운 기술 또는 비즈니스 모델(또는 둘 다)은 기존 산업을 지배하는 규제 구조와 관련된 문제를 제기하며, 기술혁신은 기존 규제 체계와 잘 맞지 않거나 긴장관계에 놓이게 된다. 이러한 갈등의 조정을 위해 각국이 “전통적인 규제방식”을 어떻게 변경시킬 것인지 관심이 모아지고 있다. 비즈니스 혁신에 의해 촉발되는 정책 교란에는 네 종류가 있다. 교묘한 회피, 면제 및 공백, 해결책이 그것이다. 예를 들어 에어비앤비는, 법적으로 차별을 두는 호스트에 의한 ‘면제’ 와 구역제, 호텔세 및 기타 규제 제도와 관련된 일련의 ‘교묘한 회피’ 정책 교란을 야기했다. 이와 같은 정책 교란에 대한 규제 기관의 정책 대응 방법에는 차단, 프리패스, 구체제, 신체제 및 신뢰이익의 보상이 있다. 에어비앤비와 우버택시의 국내 도입에 따른 법적 공백이 발생한 것과 관련해, 규제 대응 방법으로써 ‘구체제’ 또는 ‘신체제’ 이론을 적용하여 관련 국내법의 개정과 새로운 법률의 도입을 고려해 볼 수 있다.

Numerous studies have explored the influence of Airbnb on the tourism and hospitality industry. However, relatively few studies have focused on customer engagement. Considering its crucial role of boosting customer satisfaction and behavioral intentions (Harrigan, Evers, Miles, & Daly, 2017; So, King, Sparks, & Wang, 2016), there is a great need for research into Airbnb in terms of customer engagement. Therefore, this study aims to investigate customer engagement, satisfaction, and behavioral intentions among Airbnb users. This study recruited a total of 374 US Airbnb users through Amazon Mechanical Turk (MTurk), which has been increasingly adopted to collect samples in tourism and hospitality studies. Data analysis for structural equation modeling (SEM) was conducted to determine the effects of customer engagement on satisfaction and behavioral intentions of Airbnb users. The results show that customer engagement plays a crucial role in Airbnb user experiences. This study contributes to tourism and hospitality research by applying a customer engagement scale previously developed by So et al. (2016) to examine the relationship between customer engagement and behavioral intention to use Airbnb. In addition to this relationship, satisfaction was included as a mediator to better grasp the importance of customer engagement and the role of satisfaction among U.S. Airbnb users. This research also extends the current literature of Airbnb by examining, through an empirical approach, how customer engagement with Airbnb impacts its users’ behavioral intentions.

Introduction The idiom “you are what you own” has been considerably transformed into “you are what you can access”. The shift from ownership to access, the results of endless hyper-consumption, and the change in value mindsets initiated a new phenomenon, which is Sharing Economy (SE). SE has grown rapidly and refers to an entirely new business model, socio-economic ecosystem, and context for sharing the access to goods and services in technology-enabled peer-to-peer (P2P) ecosystems or consumer-to-consumer (C2C) engagement platforms. According to Botsman and Rogers (2010), SE is a result of the linkage between offline and online world, which was triggered by the society to overcome natural resources constraints. Resources in SE can be tangible (e.g., cars and homes) and intangible (e.g., expert local knowledge and labor). SE allows the sustainable use of idle resources, and it enables sellers to create new and flexible opportunities to market to consumers who experience personalized and even customized products and services at lower prices (Yang, Song, Chen, & Xia, 2017). SE opened up new horizons for a considerable number of new players across industries from a supply perspective by broadening the options for supply, which also remedies the response to peak demand. SE has given a rise to the humanization of consumer-supplier relationship in tourism and hospitality (TH), and sharing has become a mainstream practice in this context. The recent shift of customers‟ willingness to share accommodation with a host as opposed to using a private hotel room has many implications for TH (Lu & Kandampully, 2016). For example, Airbnb has become one of the most prominent competitors in hotel industry, and it enables people to lease or rent short-term accommodation including vacation rentals, apartment rentals, homestays, and even experiences via instant booking. From cash-strapped travelers to high-end business travelers, Airbnb has revolutionized the TH service in a new form of contractual relationship and gained a well-grounded popularity. Some scholars, on the other hand, argued that SE is a “fundamentally different business model” which could make it a new marketplace instead of a direct competitor in hotel industry. From this point of view, Airbnb do not compete or pose a challenge to traditional TH services but extend the concept of TH (Lu & Kandampully, 2016). Hotel industry has reactively responded to the direct, indirect, and induced effects of Airbnb to economy, and Airbnb‟s impact on hotel industry have recently been researched by several scholars (Mody, Suess, & Lehto, 2017; Priporas, Stylos, Rahimi, & Vedanthachari, 2017; Zervas, Proserpio, & Byers, 2017). Customer engagement in TH has been empirically found to enhance customers‟ service brand evaluation, brand trust, and brand loyalty (So, King, Sparks, & Wang, 2016). Guests attach great importance to motivational drivers, more meaningful “beyond-purchase” social interactions and unique experiences in authentic settings, which give rise to customer engagement beyond the service encounter. Disruptive innovation theory also states that products or services that offer alternative benefits compared to conventional attributes can transform a market and attain a critical mass, which can be observed in Airbnb‟s story (Young, Corsun, & Xie, 2017). Airbnb is successfully promoting the mottos of “Belong Anywhere” and “Don’t Go There. Live There” to their guests. The feelings of trust and belonging were negatively changed by mass production and noncustom travel experiences, and people sometimes forgot the meaning of community due to high tendency of prestige and advertising. Consumers‟ changing attitudes towards utilization and accessibility compared to ownership created an indirect need for intimate connection between people, namely human connection. Then, social concerns upon products and services gave a rise to mass-customized product and service expectations of consumers. This is where Airbnb‟s value proposition comes into play. First, it creates not only financial but also personal rewards through a “personal concierge” and a “home away from home” experience. Second, Airbnb is not a simple transaction, rather it is deemed to be a lifetime experience. So “guest experience” is at the heart of Airbnb‟s strategic position. From the “experience” point of view, SE has also opened up new rooms for service research. Service in the context of Airbnb is considered as an experience, rather than a utilitarian relation. Also, service quality has always been a critical factor in highly-competitive service industries like TH. Service quality perception is multi-faceted, and the studies focusing on it are rather limited, especially in hotel industry. These studies highlighted the complexities associated with evaluating service quality and the contribution of service process delivery on service outcomes, which results in the perception of service quality. Therefore, perceived service quality can be influenced by different internal processes and interpersonal variables. In order to study service quality in Airbnb, the types of settings in this context are to be noted. There are two main types of hosting via Airbnb: (1) remote hospitality, which refers to hosting situations in which the host does not physically share the place with the guest (e.g. booking the entire place), and (2) on-site hospitality, where the host is physically present and sharing the apartment with the guest. Mainly, on-site hospitality is an important part of the sociability within the host–guest relationship. Priporas et al. (2017) studied service quality in the context of remote hospitality, and we decided to respond to their relevant call for future research on the other type of Airbnb accommodation, which is on-site hospitality referring to “Shared Rooms” and “Private Rooms” in Airbnb‟s listings. “Shared Rooms” refer to an exact communal experience with the host, and guests sleep in a space that is shared with others and share the entire space with other people. “Private Rooms” refer to privacy, to some extent, in which guests (i) value a local connection (ii) have their own private room for sleeping and (iii) may share some spaces with others. We do expect that human connection and experience gap can be better researched with on-site hospitality existing in “Shared Rooms” and “Private Rooms”. This is because hosts design their services to create and build a relationship with their guests, leading to superior guest experiences and the so-called positive moment-of-truth. In addition to the online storytelling on hosts‟ home pages, the most important moment-of-truth is created during the guests‟ stay at the host‟s place; thus, the host plays a major role in the customer‟s perception of service and the subsequent review of the experience (Lu & Kandampully, 2016). Considering the previously mentioned “experience gap” in the literature, our research question and relevant sub-questions are as follows: • What are the antecedents of perceived service quality in Airbnb on-site hospitality? o How well does SERVQUAL suffice for measuring perceived service quality in this context? o How well the cognitive and attitudinal factors expand this measurement? o What are the additional perceived service quality factors that can be derived from guests‟ online textual reviews to remedy the “experience gap”? Literature review Cheng (2016) conducted a systematic review of SE by using co-citation and content analysis of papers, and the findings reveal three distinct research areas of SE: (1) SE‟s business models and its impacts, (2) Nature of SE, and (3) SE‟s sustainability development. Moreover, two unique areas, specifically in TH, were identified: (1) SE‟s impacts on destinations and TH services and (2) SE‟s impacts on tourists. The comparison of both literatures has revealed limited expansion in TH literature despite the fact that TH are at the frontier of SE (Cheng, 2016). Pesonen and Tussyadiah (2017) conducted cluster analysis to identify user profiles corresponding to consumer motivations for using TH services of SE. They concluded that a consumer group uses TH services of SE to make their trips more convenient, while another group uses these services mostly for social reasons. Yang et al. (2017) studied the loyalty in SE services from relational benefits perspective and concluded that confidence and social benefits have significant and positive effects on commitment in SE services. Molz (2014) introduced the term „Network Hospitality‟, which is relatively new and rooted in old traditions of welcoming strangers. Airbnb represents just one of many types of network hospitality, and in Airbnb, trust is almost shaped based on peer reviews, not solely on one-to-one peer interactions. The online review information becomes the basis for members‟ reputation in the network. The information accumulated on Airbnb‟s online platform helps both parties to establish their reputation, as well as publicizing their personalities, thereby facilitating the process of finding the best match. Moreover, there are hundreds of people working in Airbnb‟s customer service, trust, and safety departments who are devoted to ensuring the intimacy provision of trusted services. Airbnb requires all hosts to abide by their “Hospitality Standards”, which include expected levels of cleanliness, commitment, and communication. The flexibility, reliability, and consistency of Airbnb‟s service providers help them to build and maintain the relationship Airbnb enjoys with their guests and hosts (Lu & Kandampully, 2016; Zervas et al., 2017). Pine and Gilmore (1998) predicted the rise of experience in their seminal study, referring to the “experience economy” and also stating “As goods and services become commoditized, the customer experiences that companies create will matter most.” They called this as “Staging Experiences”. Also, there exists evidence in literature that providers are shifting their focus from product- and service-oriented to design of quality experiences. In terms of the glamour of SE in TH, a “more unique experience” is deemed to be second only to better pricing. Airbnb may eventually address all elements of the accommodation experience, from travel reservations to ticketing for local attractions. Consumers are looking for local authenticity in their travels. Psychological authenticity refers to emotional genuineness, self-attunement, and psychological depth (Walls, Okumus, Wang, & Kwun, 2011). If TH industry is to surpass its SE competition in terms of guest experience, it should leverage an expanded experience economy paradigm that incorporates additional dimensions (Mody et al., 2017). Authentic host-guest experiences probably only exist between like-minded and privileged members who possess high cultural capital (Cheng, 2016). With that, Walls et al. (2011) have suggested the need for researchers to identify specific dimensions “that exist in both our everyday and tourist experiences”. Both in Airbnb and traditional TH, guest satisfaction and likelihood to reuse are driven by similar factors such as quality and utility of services, trust to the host, and economic value. There are several models for measuring service quality, including SERVQUAL (Parasuraman, Zeithaml, & Berry, 1988) and SERVPERF (Cronin & Taylor, 1992). Service quality literature received widespread attention after the seminal work by Parasuraman et al. (1988) as they proposed the gap model and developed SERVQUAL (an attribute-based technique) as a tool for measuring service quality. According to SERVQUAL, service quality consists of five dimensions measured by a total of 22 items. The proposed five service quality dimensions are tangibles, reliability, responsiveness, assurance, and empathy. SERVQUAL basically requires measures of expectations and performance, and service quality is calculated from subtractions between these two components (i.e., performance [P] - expectations [E]). Regarding service quality in TH, Akbaba (2006) utilized SERVQUAL for business hotels, and Priporas et al. (2017) inquired SERVQUAL‟s applicability in Airbnb context with promising results. The major distinction between two research directions (i.e. hotels vs. Airbnb) is that even though guests expect similar core services such as clean rooms and comfortable beds, different attributes support the competitive advantage of hotels and Airbnb. While conveniences offered by hotels are unparalleled by Airbnb accommodation, the latter appeal to consumers driven by experiential and social motivations (Pesonen & Tussyadiah, 2017). Research model This research aims to identify the antecedents of perceived service quality of guests‟ in Airbnb on-site hospitality context. Our research model is presented in Figure 1, and it is subject to enhancement through the analytics of guest reviews. A survey will be developed to test the proposed research model. The items of constructs will be mainly derived from extant literature and enriched with the linguistic and textual analysis of reviews. Firstly, factors shaping expectation are predicted as per the literature and preliminary analysis of random guest reviews: (i) host‟s reputation capital (e.g., ratings and reviews), (ii) host‟s photos, (iii) guest‟s past accommodation experience, and (iv) word of mouth. Secondly, SERVQUAL part in the model is the same as proposed by Parasuraman et al. (1988). Last but not least, Airbnb is deemed to promote global geographical imaginaries (e.g., collaboration, social equity, solidarity, community, trust, reciprocity, altruism, autonomy, intimacy, and authenticity) to justify their business model (O‟Regan & Choe, 2017). Finally, regarding the guest review analysis, Airbnb has a detailed review mechanism, and we have gathered the publicly available reviews that are up to 500 words. We have observed cognitive and attitudinal dimensions within reviews through text analytics and grouped those in the research model as follows: • Intimacy: The emergence of intimacy as a commercial value in TH industry has been researched. (e.g., How well people know each other? How people occupy space together? How people share private information, family pictures, furniture choice etc.?) (Prager, 1997) • Authenticity: We focus on the existential authenticity (i.e., being one‟s true self or being true to one‟s essential nature) from guests‟ perceptions (e.g., Is Airbnb like ‘living the local life’?) (Lalicic & Weismayer, 2017) • Commitment: It refers to the consistent behavior of Airbnb hosts in terms of social and cost components. (e.g., How well hosts abide by Airbnb policies and procedures? Do hosts have ongoing effectiveness of service?) (Lu & Kandampully, 2016) • Privacy: It refers to the psychological zone to disclose personal and cultural values. Informational and physical privacy threats are important in Airbnb context (Lutz, Hoffmann, Bucher, & Fieseler, 2017). • Security: It refers to the state of being free from danger or threat. According to Yang and Ahn (2016), security in Airbnb‟s services is a more powerful antecedent of attitude toward Airbnb than significant dimensions of motivation toward SE, such as enjoyment and reputation. With that we will only elaborate on interpersonal security in Airbnb (i.e., between host and guest, not between guest and Airbnb). Conclusion SE is a fairly new and multi-disciplined field that covers open rooms for research, and specifically, Airbnb is one of the most prominent businesses in this context. The literature review presented underlies the infancy of well-grounded studies covering service quality perceptions of customers in SE. Seeking for additional dimensions from Airbnb guests‟ reviews is a novel research approach in studying customer engagement, and those dimensions shall be included in the research model. This research has certain limitations. Our perceived service quality conceptualization requires empirical validation to establish the boundaries of the construct. The guest reviews in Airbnb are subject to data quality issues. Also, reviews should contain substantial amount of words up to a certain threshold. Data collection from emerging world regions is rather tough since Airbnb is not widespread across those regions. Thus, US and European countries will be firstly taken into account, where the use of Airbnb is quite common. The study is expected to provide useful insights for TH practitioners and managers. It can underlie the factors that trigger customer engagement in this context. Cognitive/attitudinal factors are foreseen as the differentiators, which stand as the basis for service design and delivery.

The rise of the sharing economy is transforming the tourism and hospitality industry (So, Oh, and Min, 2018; Zhu, So, and Hudson, 2017). The growing popularity of Airbnb has led a number of recent studies to investigate consumer value derived from such innovative consumption model. In the context of Airbnb, research shows that perceived value motivated travelers to choose Airbnb (Mao & Lyu, 2017). However, the theoretical construct of consumer value includes multiple dimensions, such as emotional value, social value, price value, and quality value, and how each dimension contributes to consumer attitudes and behavioral intentions toward Airbnb is unexplored. Therefore, this study sets forth a national field investigation to provide a holistic understanding of consumer evaluation of various value dimensions with respect to Airbnb experiences. To empirically test the proposed model, a quantitative, national online survey was conducted using Qualtrics Online Sample. After checking the performance of the measurement model, we evaluated the results of the structural model. The results show that emotional value and quality value significantly explain overall attitude toward Airbnb, whereas, price value and social value were not significant in predicting attitude. However, price value and social value, together with overall attitude, significantly explain consumer’s purchase intention. The results show that the t values from bootstrapping were greater than 1.96, and the R2 values for endogenous variables well exceeded .26. All exogenous constructs producing effect sizes ranging from small to large. In addition, the Q2 for the endogenous latent constructs were well above the threshold, with .421 for overall attitude and .472 for behavioral intentions, thereby substantiating the structural soundness of the proposed model.