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.     

A dynamic decision support system for evaluating peer-to-peer rental accommodations in the sharing economy

Accommodation accounts for one of the biggest expenses while traveling, and deciding where to stay is often confusing and time-consuming. Fortunately, travelers have more options than ever before because of the substantial growth of the peer-to-peer (P2P) short-term rentals in the sharing economy. Designing a user-friendly system that considers travelers’ preferences in choosing the right accommodation can enhance customer satisfaction and increase profitability. We propose a dynamic decision support system based on the theory of multi-criteria decision making to assist travelers in personalizing their preferences and finding quality accommodations in the dominant P2P market that aligns with those preferences. We use the fuzzy best-worst method to measure the intensity of the user’s preferences and the fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) to score and evaluate alternative P2P rental properties. We present a case study in the P2P rental accommodations industry to demonstrate the applicability of the method proposed in this study.     

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.     

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.     

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.     

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.     

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.     

The Airbnb paradox: Positive employment effects in the hospitality industry

The purpose of this study is to examine the extent to which Airbnb supply affects employment in the hospitality, tourism, and leisure industries. Accordingly, we analyzed the effects of Airbnb supply on various sectors in the hospitality, tourism, and leisure industries in 12 major metropolitan statistical areas in the United States for the period between July-2008 and February-2018. The results showed that Airbnb supply positively affects employment in all sectors of the hospitality, tourism, and leisure industries. The magnitudes of these effects are not only statistically but also economically significant. Although prior studies have showed that Airbnb has an adverse impact on hotels' financial performance measures, our results show that employment in the hotel sector increases with increased Airbnb listings. While this outcome might be contradictory to the general conjecture, such evidence calls for a comprehensive investigation of Airbnb's overall economic impact. Research and practical implications are further discussed.     

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.     

Factors of satisfaction and intention to use peer-to-peer accommodation

To better understand the behavioral characteristics of consumers in the sharing economy, this study examines factors that influence guests’ satisfaction with a peer-to-peer (P2P) accommodation and their intention to use it again for future trips. Based on an online survey of 644 travelers living in the United States, guest satisfaction was identified as being influenced by factors of enjoyment, monetary benefits (value), and accommodation amenities. Furthermore, it was found that future intention to use P2P accommodation was again determined by enjoyment and value. By differentiating guests based on their chosen types of accommodation, the analysis revealed that social benefits influence guest satisfaction for those staying in a private room that involved cohabitation with hosts, but that this was an insignificant factor for guest satisfaction for those staying in an entire home or apartment. Directions for future research as well as implications for accommodation providers are discussed in this paper.     

Modeling Airbnb demand to New York City while employing spatial panel data at the listing level

Using spatial panel data comprising a cross section of 1,461 continuously active Airbnb listings obtained from AirDNA, as well as time series data from NYC and Company and the OECD covering the time period September 2014 to June 2016, the present study quantifies own price, cross price, and income elasticities of Airbnb demand to New York City within an empirical tourism demand framework. The particular goal of the study is to establish whether the relationship between Airbnb and the traditional accommodation industry is of a substitutional or of a complementary nature. Employing a one-way fixed-effects spatial Durbin model, it can be concluded that demand is price-inelastic for Airbnb accommodation in New York City, which is a luxury good, and that the city's traditional accommodation industry as well as neighboring Airbnb listings are substitutes for the investigated Airbnb listings. The estimation results are robust against several alternative specifications of the regression equation.     

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.     

Experiencing P2P accommodations: Anecdotes from Chinese customers

This study explores the key dimensions and attributes of Chinese customers’ experiences with peer-to-peer (P2P) accommodations through Airbnb in China. Thirty-four in-depth interviews were conducted with Airbnb customers. Results suggest that seven dimensions underpin the customer experience with P2P accommodations: physical utility, sensorial experience, core service, guest-host relationship, sense of security, social interaction, and local touch. This indicates that unlike traditional commercial hotels, P2P accommodations appeal to customers to a larger extent for their social and cultural characteristics. Implications are provided for stakeholders, including P2P accommodation practitioners and users, to co-create experiential value.     

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.     

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。     

Pricing in the sharing economy: a hedonic pricing model applied to Airbnb listings

ABSTRACT

This paper examines the impact of a variety of variables on the rates published for Airbnb listings in five large metropolitan areas in Canada. The researchers applied a hedonic pricing model to 15,716 Airbnb listings. As expected, the results show that physical characteristics, location, and host characteristics significantly impact price. Interestingly, more reviews are associated with a drop in price. This information is useful to hosts who are forming a pricing strategy for their listings as well as for Airbnb, who needs to support them. The paper raises important questions about pricing in the sharing economy and suggests avenues for future research in this area.     

What prevents consumers that are aware of Airbnb from using the platform? A mixed methods approach

The hospitality sector is now characterised by the co-existence of traditional providers and sharing economy enterprises. It is important to better understand what prevents the use of peer-to-peer accommodation rentals in the tourism marketplace. Adopting a mixed-methods approach, this study first examines travellers’ Airbnb use constraints, and then profiles 252 Airbnb non-users based on their constraints and characteristics. The findings suggest that travellers do not use Airbnb because of distrust in the providers, in the platform and in other users, as well as perceived risk and unfamiliarity. Loss of service quality, lack of local experience, legal and regulatory issues, and disinterest also prevented consumers to book Airbnb accommodations. A cluster analysis divided non-users into three segments: Traditional travellers, Sharing economy misbelievers and Airbnb prospective users. Significant differences based on age confirmed that young travellers are more confident in using peer-to-peer accommodation platforms and more interested in the philosophy.     

Communicating quality while evoking loss – How consumers assess extra charges in the Airbnb marketplace

The rise of the sharing economy has allowed consumers to choose from hundreds of thousands of diverse accommodations. In this article, we explore the impact of price partitioning on demand. Our findings reveal that partitioning the price into different elements can have a positive impact on demand. We argue that when the price is partitioned into different fees, it draws attention to the rationale behind the fees – such as additional cleaning. While the presence of the fees acts as a signal, we draw upon prospect theory to argue that the amount of the fee is viewed as a loss and thus has a negative impact on demand. We test our arguments using data on Airbnb's across the whole United States and find that price partitioning positively impacts demand, but the costs themselves have a negative impact on demand.