Power dynamics in peer-to-peer accommodation: Insights from Airbnb hosts

This study explores power dynamics in peer-to-peer (P2P) accommodation by examining how they manifest in the host-guest relationship. In so doing, it advances understanding on the role of hosts in the P2P practice and contributes insights on the factors conditioning the reciprocity of the P2P exchange. Drawing from power theories, the study uncovers how the interdependencies among hosts, guests and platforms influence power constellations emanating from P2P accommodation growth and reflexively redefine host practice. Specifically, the study illustrates how hosts are attempting to resist power imbalances characterising the exchange and how the dynamic environment of P2P accommodation leads to distinct representations of host types. The study makes explicit a conceptual framework that captures the power shifts noticeable in P2P accommodation that may be of theoretical and practical value to academics and policymakers alike.     

The construction of home feeling by Airbnb guests in the sharing economy: A semantics perspective

Although the literature of peer-to-peer accommodation is increasingly recognizing the importance of home feeling, little has been done to theorize the construction of home feeling and its impacts on Airbnb guests’ future intention. To fill in this gap, this study systematically unpacked how Airbnb guests construct the feeling of home. A total of 42,085 review comments containing the feeling of home from three major cities in the USA were analyzed from a semantics perspective. Based on our findings we conceptualize home feeling as a PASS_h process, which contains multiple dimensions: physical and spatial, social, and affective, coupled with hospitality. Essentially, the home feeling with the interaction of these dimensions fulfills the daily hybrid needs of the guests.This article also launches the Annals of Tourism Research Curated Collection on Peer-to-peer accommodation networks, a special selection of research in this field.     

Exploring the effect of Airbnb hosts' attachment and psychological ownership in the sharing economy

Previous research on the sharing economy has not typically focused on organizational structure and its management in spite of the fact that the essence of recent peer-to-peer business practices is the collaboration of online platforms and sharable assets owned by market peers. This paper critically examines a theoretical model to explore how these market partners engage in this platform organization and how their perceptions of attachment and ownership are established within the new organizational structure. The results of structural equation modeling applied to 224 Airbnb hosts indicate that attachment to a platform firm plays a vital role in achieving a sense of psychological ownership that ultimately influences citizenship behaviors toward the organization as well as toward peer hosts. The results suggest that the newly formed structure should acknowledge an establishing mechanism of attachment and psychological ownership in partnering with individual service providers in its operational management.     

Brand personality of Airbnb: application of user involvement and gender differences

ABSTRACT

In this study we utilized the concept of brand personality to determine how travelers perceived Airbnb as a lodging brand and investigated the effect of involvement level (low versus high) on view of brand personality. As a viable segmentation variable, this study also utilized the interaction effect to examine how gender affects consumers’ involvement level. Significant differences were observed between travelers with high and low involvement in terms of the dimensions of sincerity, excitement, competence, and ruggedness. In addition, we found the interaction effect to be significant, indicating that level of involvement is higher in female travelers than in male travelers. This research will provide meaningful marketing insights for target marketing and positioning based on consumer involvement and gender within the context of Airbnb.     

Determinants of Airbnb prices in European cities: A spatial econometrics approach

We examine the determinants of Airbnb prices in 10 major EU cities, focusing on the role of location. The results confirm that attributes related to size, quality, and location are all significant drivers of Airbnb rates. Novel indices based on TripAdvisor data are used to measure the attractiveness of neighbourhoods, and the results show a more robust impact on price than standard location variables based on selected points of interest. The analysis confirms that Airbnb prices are spatially dependent, requiring the implementation of spatial regression models. Following recent studies on spatial econometrics, we examine various spatial models, including specifications with multiple sources of spatial dependence. The results show significant differences between the coefficients estimated with OLS and the various spatial models, especially in the case of location-specific variables. As well as having managerial and policy implications, our study contributes to the hedonic price literature by providing a methodological guide on spatial regression models.     

Dynamic pricing and revenues of Airbnb listings: Estimating heterogeneous causal effects

This paper investigates the extent to which the implementation of intertemporal price discrimination affects Airbnb listings’ revenue. We found that on average, a price surge (i.e., increasing the price as we approach the date of service consumption) has an adverse effect on revenue. However, the magnitude of such effect exhibits significant heterogeneity among listings. Through the application of generalized random forests, a causal machine learning technique, we identify exacerbating and moderating treatment modifiers and shed light on the listing dimensions that cause price surges to be particularly detrimental for hosts’ revenues.     

Price and RevPAR determinants of Airbnb listings: Convergent and divergent evidence

This paper explores the performance determinants of Airbnb listings, analyzing three research questions. First, the study investigates the different effects generated by the antecedents on price and revenue; second, it ranks different groups of variables; third, it distinguishes between private rooms and entire homes or apartments. These research questions are addressed by analyzing Airbnb listings in Milan, a business city where the sharing economy is growing fast. In particular, the study will use the monthly data of all Airbnb listings in Milan recorded by AirDNA during the period from November 2014 to June 2019, which consists of 323,184 total observations. Some hedonic price models are calculated, adding the Shapley value approach. Empirical findings show some important differences between price and revenue determinants. Furthermore, listing type and size, along with location and seasonality, are by far the most important factors that explain performance differentials among Airbnb properties.     

Spanning across the boundary of Airbnb host community: a network perspective

The success of Airbnb has not only provided people with an alternative way of managing their living spaces but also created a rapidly growing number of Airbnb host communities. Guided by boundary spanning theory, this study examines how Airbnb host online communities evolve through novel organizational forms. Data for this study were collected from an online Airbnb host community from which two stages of analysis were performed. These included social network analysis and content analysis. The findings indicate that the online community functions as an informal specialized sub-unit of Airbnb and that hosts’ roles in the organization involve a number of boundary spanning aspects. The research contributes to an evolving understanding of hosts in the peer-to-peer (P2P) accommodation literature as well as extending the theory of boundary spanning in its application to the sharing economy context.     

The evolution of trust in Airbnb: A case of home rental

Airbnb, a leader of P2P accommodation markets, has acknowledged that “trust is what makes Airbnb work” and has implemented several trust indicators over the years: reputation system, impression formation, and certification. We evaluate the changes in these indicators over time: 1. the modification of the reputation system, 2. the removal of hosts’ photos from the main search screen, and 3. the introduction of the Superhost program. We find that the change of the rating system was associated with a small, yet significant, reduction in ratings, that the removal of the hosts’ photos might have eliminated the price premium of trustworthy images, and that Superhost certification involves a price premium, but does not seem to compensate for established reputation.This article also launches the Annals of Tourism Research Curated Collection on Peer-to-peer accommodation networks, a special selection of research in this field.     

共享民宿空间集聚特征及其影响机制研究——以北京市Airbnb为例

在构建“双循环”新发展格局的时代背景下,共享民宿的科学布局对有效释放旅游市场需求潜力,促进国内大循环的畅通和发展,具有积极的意义。本文以北京市Airbnb为例,综合运用空间分析和地理探测器等方法探究了共享民宿的空间集聚特征及其影响机制。结果表明：（1） Airbnb在空间上呈显著的集聚分布,整体上表现出“大集聚、小分散”的空间形态,形成4个明显的高密度核心区;（2） 置信度高于99 %的热点区所占比重最大,主要集聚在市中心周围至东四环附近地区,且Airbnb与其他相关地理要素存在不同程度的空间集聚;（3） 休闲娱乐设施数量、距市中心距离和公共服务设施数量等因素的解释力较强,双因子交互作用的解释力均强于单因子,休闲娱乐设施数量对因子交互作用的影响最大;（4） 在影响机制中,房东作为供给者,其选址行为和主观意愿为基础因素;房客作为需求方,其多样化的需求成为主导因素;政府作为监管者,其宏观调控举措是调节因素;平台作为管理者,其战略决策和市场推广是引导因素。不同利益主体之间的耦合交互与权衡制约,各类要素在不同发展阶段的综合作用,最终形成了影响共享民宿空间集聚特征的合力。     

Exit and transition: Exploring the survival status of Airbnb listings in a time of professionalization

This study analyzes the survival status of shared and non-shared listings in the peer-to-peer accommodation market. Using a large data set from Airbnb in Beijing, we identify 8640 shared listings and 50,741 non-shared listings. We then investigate the exit event and the identity transition event for both types of listings by applying a discrete-time hazard model. Our results suggest that, for the exit event, the two types of listings show significant differences in terms of survival determinants, including response time, tourism specialization, market volume, professionalization, and Covid-19. For the identity transition event, we find that internal flow exists in the market, mainly from shared listings to non-shared listings, and this flow is influenced by certain factors (i.e., capacity, facility, rating, reviews, minimum stay, service quality, tourism specialization, market volume, platform professionalization, and Covid-19).     

Stars vs lemons. Survival analysis of peer-to peer marketplaces: the case of Airbnb

This paper analyses the determinants of listings' survival on peer-to-peer marketplaces. Working on a dataset of Airbnb listings in Ibiza, we implement survival analysis to estimate the relationship between listings' key attributes and the probability to leave the platform. In addition, we highlight the importance of user-generated content to reduce the asymmetry of information and prevent adverse selection. Results confirm that listings' characteristics, location, degree of local competition and hosts' managerial skills, significantly affect the survival chance. Moreover, we found that low quality listings (proxied by the customer rating) are intended to disappear: the reviewing system successfully signals the quality on this market and drive the market selection process.     

The effects of Airbnb on hotel performance: Evidence from cities beyond the United States

Although Airbnb's impact on hotels has been quantified for major hotel markets in the United States, these effects have not been quantified in international hotel markets. Accordingly, the purpose of this study is to examine the effects of Airbnb listings on key hotel performance metrics in an international context. In particular, we examine the effects of Airbnb listings on hotel revenue per available room (RevPAR), average daily rate (ADR), and occupancy rate (OCC) in major international hotel markets, namely London, Paris, Sydney and Tokyo. The results show that Airbnb listings in these major cities have been increasing more than 100% year over year and that the effect of Airbnb on hotel RevPAR and OCC is negative and statistically significant. In particular, a 1% increase in Airbnb listings decreases hotel RevPAR by between 0.016% and 0.031% in these hotel markets. The implications of these findings for destinations and hoteliers are discussed.     

Trust and reputation in the sharing economy: The role of personal photos in Airbnb

‘Sharing economy’ platforms such as Airbnb have recently flourished in the tourism industry. The prominent appearance of sellers' photos on these platforms motivated our study. We suggest that the presence of these photos can have a significant impact on guests' decision making. Specifically, we contend that guests infer the host's trustworthiness from these photos, and that their choice is affected by this inference. In an empirical analysis of Airbnb's data and a controlled experiment, we found that the more trustworthy the host is perceived to be from her photo, the higher the price of the listing and the probability of its being chosen. We also find that a host's reputation, communicated by her online review scores, has no effect on listing price or likelihood of consumer booking. We further demonstrate that if review scores are varied experimentally, they affect guests' decisions, but the role of the host's photo remains significant.     

Price determinants of sharing economy based accommodation rental: A study of listings from 33 cities on Airbnb.com

The advent of the “sharing economy” challenges not only the business of hotel industry but also the theories and models based on the conventional hotel industry. A key dimension of the hospitality industry is pricing. The aim of this study is to identify the price determinants of sharing economy based accommodation offers in the digital marketplace. Specifically, a sample of 180,533 accommodation rental offers in 33 cities listed on Airbnb.com is investigated using ordinary least squares and quantile regression analysis. Twenty-five explanatory variables in five categories (host attributes, site and property attributes, amenities and services, rental rules, and online review ratings) are explored for the intricacies of the relationships between pricing and its determinants.     

Understanding repurchase intention of Airbnb consumers: perceived authenticity,electronic word-of-mouth,and price sensitivity

ABSTRACT

The purpose of this paper is to extend the research on consumer repurchase intention, perceived value, and perceived risk into the realm of the peer-to-peer economy, specifically in the context of Airbnb. A total of 395 surveys were collected in Canada and the United States. The results showed that perceived risk negatively impacts Airbnb consumers’ perceived value and repurchase intention while perceived value positively enhances their repurchase intention. Interestingly, price sensitivity was found not to reduce customers’ perceived risk but can improve their perceived value and positively influences them to repurchase the Airbnb products. Perceived authenticity was found to have a significant effect in reducing Airbnb consumers’ perceived risk and positively influencing their perceived value. Electronic word-of-mouth has a positive effect on repurchase intention as well as perceived value whereas it negatively affects perceived risk. Theoretical and managerial implications are discussed and future study directions are offered.     

TO SHARE OR TO EXCHANGE: An analysis of the sharing economy characteristics of Airbnb and Fairbnb.coop

Many organizations seek to position themselves as part of the sharing economy, due to positive conceptual connotations; however, in reality, some may more closely represent the exchange rather than the sharing economy. This research analyses the extent to which Airbnb and Fairbnb.coop represent the sharing economy by examining the characteristics of the sharing economy. We utilize a Sharing Index (SI) and a Sharing Economy Continuum (SEC) to measure each organization’s degree of sharing and exchange. The analysis suggests that Fairbnb.coop is a stronger example of the sharing economy than Airbnb. This study offers a more robust characterization of the sharing economy and offers tools to help businesses assess and improve their business practices to more accurately align with the true sharing economy.     

Core and supplemental elements of hospitality in the sharing economy: Insights from semantic and tonal cues in Airbnb property listings

Advances in peer-to-peer sharing, made popular by platforms like Airbnb, have altered previous conceptualizations of the lodging hospitality product. This study performs semantic and tonal analyses on a large-scale dataset collected from Airbnb. Our results support a concept of lodging hospitality that comprises core products and services, supplemental customer care, and a third factor we term ‘host sharing.’ Furthermore, the study offers insight into the topics and rhetorical tactics currently defining lodging hospitality marketing on the Airbnb platform. These findings can be used to provide guidance for Airbnb hosts to provide suitable information in their listings.