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 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.     

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.     

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.     

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.     

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.     

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.     

Using segmentation to compete in the age of the sharing economy: Testing a core-periphery framework

Airbnb has emerged as a credible competitive threat to the hotel industry. Consequently, hotel brands are having to rethink the experiences they provide to customer in an increasingly competitive environment. Despite these trends in the industry, experience-related research that examines and informs these developments remains under-represented in the hospitality and tourism literature. The present study offers a systematic approach to examine the potential differences in experiential consumption in the accommodations industry. Using a multiple-group analysis approach, it examines the moderating effects of individual characteristics and situational factors on the nature and dynamics of experiential consumption in the accommodations industry. The findings of the study culminate in the core-periphery framework of the hospitality consumption experience that can provide a relevant theoretical lens for future research into the different sectors and types of experiences within the hospitality and tourism industry. The study also outlines important implications for the hotel industry’s strategic experience design initiatives, from the standpoint of product development, the segmentation, targeting and positioning (STP) process, and marketing communications.     

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.     

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.     

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).     

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.     

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.     

A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism

Online consumer reviews have been studied for various research problems in hospitality and tourism. However, existing studies using review data tend to rely on a single data source and data quality is largely anecdotal. This greatly limits the generalizability and contribution of social media analytics research. Through text analytics this study comparatively examines three major online review platforms, namely TripAdvisor, Expedia, and Yelp, in terms of information quality related to online reviews about the entire hotel population in Manhattan, New York City. The findings show that there are huge discrepancies in the representation of the hotel industry on these platforms. Particularly, online reviews vary considerably in terms of their linguistic characteristics, semantic features, sentiment, rating, usefulness as well as the relationships between these features. This study offers a basis for understanding the methodological challenges and identifies several research directions for social media analytics in hospitality and tourism.     

Mapping the progress of social media research in hospitality and tourism management from 2004 to 2014

ABSTRACT

One hundred and five articles on social media in hospitality and tourism during 2004–2014 were identified from three databases and seven journals. Seven dimensions were used for analysis. Results indicated that social media research in hospitality and tourism is in its early stages with two turning points. The number of articles rose dramatically in 2010 and unexpectedly dropped in 2014. Research gaps are apparent in several industry sectors in topics beyond online reviews and in research methods, where literature reviews suffer from small numbers and few prominent researchers. Implications and future research directions are also discussed.     

Learn from the past and prepare for the future: A critical assessment of crisis management research in hospitality

Given the substantial impact of crisis on the hospitality industry, crisis and crisis management have drawn attention from scholars. While each study makes a significant contribution to the existing knowledge of crisis management in hospitality, the fragmented perspective of each study makes it difficult to identify the key findings and unsolved problems. This paper presents a synthesis and critical assessment of state-of-the-art crisis management research in hospitality. It categorizes articles based on a three-stage framework covering pre-crisis planning, mid-crisis management, and post-crisis recovery. Two main perspectives in the literature are identified: one from hospitality service providers and one from stakeholders. Core research topics and concepts in each stage and perspective are reviewed. In addition, this paper proposes four major directions for future research: crisis management from stakeholders’ perspectives, integrative research, causal and behavioral research, and theoretical enhancement. It discusses the theoretical and practical implications of this study.     

Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model

ABSTRACT

The sharing economy literature has largely concentrated on the examination of peer-to-peer accommodation platforms such as Airbnb, with little attention paid on other innovations in collaborative consumption. This study investigates consumer adoption of the Uber mobile application through lenses of two theoretical models – Diffusion of Innovation Theory and Technology Acceptance Model. The results suggest that relative advantage, compatibility, complexity, observability, and social influence have a significant influence on both perceived usefulness and perceived ease of use, which in turn lead to subsequent consumer attitudes and adoption intentions. This study demonstrates the integration of the two classic adoption theories.