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.     

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.     

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.     

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.     

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.     

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.     

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.     

A pathway to consumer forgiveness in the sharing economy: The role of relationship norms

The emergence of peer-to-peer accommodations has revolutionized the hospitality industry. Yet, research on peer-to-peer service failures and consumer forgiveness remains scant. This paper shows that relationship type—whether communal ("Airbnb host") or exchange ("hotel")—influences consumer forgiveness in a post-recovery context. Across five studies, this research demonstrates how peer providers (focusing on communal norms) versus conventional providers (focusing on exchange norms) influence consumer forgiveness and their responses to service recovery efforts. Our findings indicate that focusing on social service recovery is particularly effective for Airbnb hosts. These findings have important implications for crafting effective service recovery strategies based on the type of accommodation provider-customer relationship. Finally, our findings can also help peer-to-peer and conventional hospitality providers alleviate consumers’ negative responses to service failures.     

Effect of crowd wisdom on pricing in the asset-based sharing platform: An attribute substitution perspective

Technological advancement has led to the emergence of online platforms fueled by the sharing economy across various industries. This study focuses on Airbnb - a specific asset-based sharing platform in the hospitality industry. Applying the theory of attribute substitution, we explore the wisdom of the crowd manifested in online reviews, in impacting pricing. We found that online review valence and volume have a positive association with room price. Depending on the crowdedness of the location this association is stronger or weaker. Customers care more about room popularity (volume) in a certain area when the fast system of decision-making is triggered. When, however, the slow system is triggered, customers consider the crime rate of a location (valence). Findings show how environmental stimuli and customer reviews decide room price - a variable that was decided traditionally by companies (e.g., hotels). The research furthers our understanding on asset-based platforms in the sharing economy.     

Measuring perceived risk in sharing economy: A classical test theory and item response theory approach

Sharing economy is considered as a disruptive innovation in the Internet age and inevitably brings huge concerns and risks for tourists. This study aims to develop a multidimensional scale to understanding the tourist risk perception in the sharing economy (TPRSE). First, focus group interviews, and online text analysis were conducted to elicit the initial items. Second, pilot survey involving a sample size of 218 was conducted, confirmatory factor analysis (CFA), and item response theory (IRT) were applied to refine this preliminary item pool. Third, the TPRSE scale was further validated using the CFA and IRT (n = 745). The TPRSE scale was successfully developed and validated, which including five dimensions of financial risk, social risk, privacy risk, performance risk and physical risk. This study advances the theories of risk perception in the context of sharing economy and provides management strategies to reduce perceived risks in Airbnb accommodations.     

40 years of sharing economy research: An intellectual and cognitive structures analysis

This study aims to analyze the intellectual and cognitive structures of the sharing economy as a field of research. Adopting an integrated bibliometric approach of citation, co-citation, and co-word analysis, this study analyses 941 articles published on Web of Science from 1978 to 2019. Findings reveal that despite there being a latent concentration in citations distribution, the ascending and descending influence patterns discovered over time indicate a dynamic flow and healthy growth of the field. The analysis of the intellectual structure identifies four main areas of research, with hospitality and tourism being the most developed, and the journals about hospitality being the preferred channel for research into the sharing economy. Finally, for the cognitive structure analysis, in-depth strategic diagrams, thematic evolution, and trend analysis disclose some research gaps. Thus, we contribute to the sharing economy literature by inductively synthesizing, and organizing SE research, and by proposing future research directions.     

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.     

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.     

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.     

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.     

The eruption of Airbnb in tourist cities: Comparing spatial patterns of hotels and peer-to-peer accommodation in Barcelona

In recent years, what has become known as collaborative consumption has undergone rapid expansion through peer-to-peer (P2P) platforms. In the field of tourism, a particularly notable example is that of Airbnb. This article analyses the spatial patterns of Airbnb in Barcelona and compares them with hotels and sightseeing spots. New sources of data, such as Airbnb listings and geolocated photographs are used. Analysis of bivariate spatial autocorrelation reveals a close spatial relationship between Airbnb and hotels, with a marked centre-periphery pattern, although Airbnb predominates around the city's main hotel axis and hotels predominate in some peripheral areas of the city. Another interesting finding is that Airbnb capitalises more on the advantages of proximity to the city's main tourist attractions than does the hotel sector. Multiple regression analysis shows that the factors explaining location are also different for hotels and Airbnb. Finally, it was possible to detect those parts of the city that have seen the greatest increase in pressure from tourism related to Airbnb's recent expansion.     

The uniqueness of entrepreneurship in the sharing accommodation sector: Developing a scale of entrepreneurial capital

Hosts on sharing lodging platforms are viewed as an emerging form of entrepreneurs. This study aims to define entrepreneurship and entrepreneurial capitals and generate a multidimensional scale of entrepreneurial capitals for sharing accommodations (ECSA). A rigid procedure with three steps was followed to develop and validate this scale. An initial pool of items was provided through content analysis of 59 written surveys and literature review in Step 1. In Step 2 exploratory factor analysis (n = 150) was applied to further purify and refine this preliminary item pool. The 17-item ECSA scale was validated using confirmatory factor analysis (n = 328) in Step 3. Results support ECSA which covers four perspectives (i.e., financial, social, intellectual, and human capitals). The ECSA scale enriches the research body of entrepreneurship by examining an emerging business phenomenon. And it prepares practitioners for becoming micro-entrepreneurs on sharing lodging platforms.     

The role of the rural tourism experience economy in place attachment and behavioral intentions

This study aims to empirically explore the effect of the experience economy on place attachment and behavioral intentions through emotions and memory. To do so, the rural tourism context was selected as it not only provides small accommodation units in the countryside, but is also related to a set of possible activities involving both passive and active participation by guests. The survey was conducted using a self-administered questionnaire distributed to individuals experiencing rural holidays in the South of Portugal. A convenience sample of participants, resulting on 222 usable questionnaires, was employed to test the model. The partial least squares (PLS) approach was used to treat the data. The findings demonstrated the role of pleasant arousal and memory as mediators between experience and behavioral intentions. An excited and pleased guest is more likely to memorize the experience. Nevertheless, the effect of pleasant arousal and memory on place attachment was not proven. The findings also lead to managerial implications, limitations and suggestions for future research.     

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.     

Exploring the Role of Travel and Tourism in Sharing Economy Activities: A Case Study of South Korea

This study explores the role of travel and tourism in sharing economy activities by using a case study of Seoul, South Korea. The findings reveal 1) significant associations between respondents’ demographic and socio-economic characteristics and their participation level in diverse sharing economy activities; 2) significant differences in future intention to participate in diverse sharing economy activities among groups; and 3) interest in travel and tourism was most strongly related to future intention to participate in diverse sharing economy activities. Policy making implications of the sharing economy focused on the role of travel and tourism are discussed in the conclusion.