The current state of academic research into peer-to-peer accommodation platforms

The “sharing” phenomenon represents one of the hottest trends in the hotel and tourism industry. As the number of academic papers in this field is growing, now appears to be an appropriate time to take stock of the research. This article contributes to filling this gap by illustrating the state of peer-to-peer accommodation platforms (P2P APs) and identifying useful future research avenues. The paper is structured around two research questions: What is the state of the literature investigating P2P APs? What are some promising future research areas concerning P2P APs? This study proposes eight topics, while the literature review includes 189 published papers. After classifying the findings, this paper presents and discusses some pitfalls, as well as suggests implications for future research, while it also outlines specific research opportunities that are particularly suited for each of the eight topics.     

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.     

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.     

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.     

Clusters of topics and research designs in peer-to-peer accommodation platforms

This article is a literature review exploring academic papers focused on peer-to-peer accommodation platforms (P2P APs). The sample includes 189 published works indexed in the Scopus and Web of Science databases, identified using 72 queries. The research question underlying the study is centered on clusters of topics and their research designs. Using a cross-citation approach, nine clusters are identified, and a research map is proposed structured around six blocks. These include i) conceptual papers analyzing the sharing economy (cluster 1); ii) demand-side papers based on the consumer behavior approach (cluster 2); iii) host papers exploring spatial patterns (cluster 3) and researching determinants of performance (cluster 4); iv) host-guest relationships, based on Airbnb (cluster 5) and on noncommercial platforms (cluster 9); v) social impact of P2P APs (cluster 6), and vi) effects generated on hotels, including economic impact (cluster 7) and comparison of Airbnb and hotel strategies (cluster 8).     

Investigating the whole picture: Comparing the effects of Airbnb supply and hotel supply on hotel performance across the United States

This study examines and compares the extent to which Airbnb and hotel supply affect key hotel performance measures in the United States. The results show that although both Airbnb and hotel supply adversely affect hotel revenues (i.e., RevPAR), the magnitude of the impact of hotel supply on RevPAR is much larger than that of Airbnb. Airbnb adversely affects hotel room prices (i.e., ADR), however; it does not affect occupancy rates (i.e., OCC). Yet, increasing hotel supply negatively affects OCC but not ADR. The results from the state-level analyses further showed that the negative effects of Airbnb and hotel supply on RevPAR, ADR and OCC persist only in states with high hotel supply. Analyzing the joint effects of Airbnb and hotel supply on hotel performance in a manner that is both geographically-comprehensive and spatially-meaningful, this study provides a more complete and nuanced understanding on the economic dynamics of the accommodation industry.     

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.     

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.     

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。     

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.     

When users decide to bypass collaborative consumption platforms: The interplay of economic benefit,perceived risk,and perceived enjoyment

Bypass, which consists of intentionally circumventing a collaborative platform in the final transaction phase, represents a threat for commission-based platforms. This paper examines collaborative consumers' motivations to bypass and proposes a conceptual model explaining bypass intention. Multigroup analysis of 549 UK respondents (310 accommodation-rental users; 239 ride-sharing users) using PLS-SEM shows that perceived enjoyment and perceived risk are strong predictors of bypass intention. Our findings also confirm the significant impact of economic benefit influencing bypass decisions, both directly and indirectly, by reducing perceived risk and increasing perceived enjoyment. This study extends the literature on collaborative consumers’ bypass motivations, identifying an interplay of utilitarian motive (economic benefit), hedonic motive (perceived enjoyment), and perceived risk. It also contributes to the field of misbehaviors in hospitality and tourism, by showing empirically the link between pleasure and deviance. Finally, it helps platforms to determine the types of exchange that are more prone to bypass.