Exploring hotel guests' perceptions of using robot assistants

The growing popularity of robot services blurs the boundaries of robotics and human life. Concomitant to the trend, many hotel brands have adopted a robot-based automation system in their properties. This study attempted to understand the underlying perceptions of the hotel guests' robot-using behaviors. A sample of 494 potential users of a hotel robot assistant was examined and analyzed. The result showed six factors, including three functional aspects (i.e., facilitating conditions, performance expectancy, and innovativeness) and three emotional aspects (i.e., social presence, hedonic motivation, and perceived importance). Moreover, this study categorized the respondents into cohesive groups that show similar characteristics. Based on different levels of perceptions and demographic information, four clusters were named as ‘The ordinary,’ ‘Enthusiastic adopter,’ ‘Tech laggard,’ and ‘Value seeker.’ The result of this study is expected to help the hotel industry to better target potential customers by understanding the different types of users of robotic technology.     

Peer-to-peer interactions: Perspectives of Airbnb guests and hosts

In peer-to-peer (P2P) accommodation settings such as Airbnb, social interactions between peers are distinctively different from those between guests and employees in conventional lodging establishments. This study focuses on a reciprocal aspect of social interactions in P2P accommodations and aims to: 1) explore how guests and hosts perceive online and face-to-face interactions between them and 2) investigate the association between P2P interactions and some outcome variables (encounter satisfaction, word-of-mouth intention, and continuous intention to use) based on the roles of guest and host. A total of 503 responses from an online research panel were analyzed. The results show that guests perceive overall interaction experiences more positively than do hosts. Moreover, guests and hosts place weight on different interaction factors that contribute to their satisfaction and behavioral intentions. This study sheds light on the reciprocal interactions between guests and hosts, providing important theoretical and practical implications for the P2P lodging experience.     

A Lefebvrian analysis of Airbnb space

This paper draws from Lefebvre's spatial triad theory in examining Airbnb space, contributing to knowledge on how space discourses are constructed and in turn internalised in host and guest practices. The study identifies tensions in host-guest-platform relations, illustrating attempts to professionalise and standardise hospitality practices. We conceptualise Airbnb as a space of multiple meanings that reflects the transitionary nature of contemporary hospitality wherein notions, roles and practices are redefined. Conclusively, this paper advocates further research on hospitality's spatial dimensions to uncover the perplexed relations, inherent inequalities and potential opportunities characterising postmodern tourism.     

Understanding the drivers of Airbnb discontinuance

Previous literature on consumer decision-making and innovations (e.g. Airbnb) largely concentrates on positive consumer responses and is prone to pro-innovation bias, while consumer discontinuance has yet to be considered. This research aims to investigate factors leading to consumer discontinuance in Airbnb usage by analysing online reviews. Data were analysed using an inductive qualitative content analysis approach. The findings distinguish between online and offline service issues as key determinants of discontinuance, and a graphic representation of discontinuance drivers is provided to better understand this phenomenon. This research highlights the importance of discontinuance as a new research stream and provides a grounded understanding of its antecedents.     

Spatial price mimicking on Airbnb: Multi-host vs single-host

This paper studies the existence of two different supply operators in the peer-to-peer accommodation rental market for the city of Madrid. We specifically analyse spatial dependencies in price formation and whether the so-called professional hosts (i.e. those who have several Airbnb listings) set prices differently from single-property hosts. To this end, hedonic price models are estimated with and without spatial price dependence. Listings’ structural characteristics and accessibility measures to transportation hubs and sightseeing spots are considered in the regressions. Results provide clear evidence that price mimicking is higher among non-professional hosts whereas professional hosts set prices more independently.     

Motivators behind information disclosure: Evidence from Airbnb hosts

Extensive studies have researched on the determinants of user information disclosure. This study extends current research by switching into peer-to-peer property rental platforms and highlights the information disclosure behavior of hosts (sellers). We construct a conceptual framework and collect a unique longitudinal dataset from Airbnb to examine the determinants of hosts' decisions to disclose information. The empirical results suggest that getting more reviews, higher ratings, and receiving more informative or readable reviews motivate hosts to disclose more information, especially for low permission relevant information. Moreover, property quantity negatively moderates the relationship between the reviews hosts received and their information disclosure intention. This study concludes by presenting theoretical and managerial implications for both research and practice.     

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 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.     

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.     

Treatment of the Airbnb controversy by the press

Airbnb is one of the most transformative developments in the traditional accommodation system. Due to the social impact it entails, Airbnb is currently a present topic in the press, although studies on how Airbnb is treated in the press are very scarce. Thus, this article aims to analyse the treatment of Airbnb controversial issues in the press and its evolution. The analysis method is first to follow the evolution from 2016 to 2018, second, to conduct a computerised quantitative content analysis, and finally to analyse the importance of information published through compositional data analysis. Results show that topics appearing most in the news are legal issues and regulations followed by gentrification, new forms of tourism and sharing economy, mainly being treated from a negative perspective, although are evolving towards a more positive vision. Results can be useful for local and national authorities to understand and manage this phenomenon.     

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.     

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.     

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.     

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.     

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.     

Destination image analytics for tourism design: An approach through Airbnb reviews

This study embraces destination image analytics, design thinking and peer-to-peer accommodation services. The paper aims to support marketers in rethinking the way they design destination experiences and marketing strategies by synergising with contemporary trends in the peer-to-peer accommodation sector and help integrate them into destination marketing systems. Thus, a holistic process is developed to reveal how destination image is constructed that applies compositional data analysis on almost one million Airbnb reviews from four Spanish urban destinations on a temporal basis (two consecutive periods). The designative aspect of image distinguishes the destinations, and temporal image trends are observed. These insights allow marketers to re-formulate and design marketing and experience strategies that align with the needs and experiences of contemporary tourists.     

Tackling the complexity of guests' food waste reduction behaviour in the hospitality industry

Food waste reduction represents a significant sustainability and economic problem and is being effectively examined by researchers, organisations, and governments around the world. Yet, guests' decision formation for such sustainable behaviours has not been sufficiently investigated in the hospitality and tourism industry. This study fills such gap, utilising advanced approach to demonstrate how a combination of demographic and socio-economic, attitude and values, and anticipated feelings can stimulate guests' food waste reduction behaviour (FWRB). A conceptual framework has been developed according to complexity theory, which was tested utilising fuzzy-set qualitative comparative analysis (fsQCA) of 1295 guests. Our empirical findings revealed that no single variable is sufficient to predict guests' behaviours towards food waste reduction, but five casual recipes were identified for stimulating high FWRB. These findings help practitioners to develop new strategies and approaches to stimulate guests' behaviours towards food waste reduction.     

Disruptive innovation,innovation adoption and incumbent market value: The case of Airbnb

The purpose of this article is to analyze the market value impact of actions taken in response to disruptive innovation; specifically, actions that incumbent lodging firms implement to adopt the innovation of peer-to-peer trading-based accommodation rental. As incumbent firms need to device strategies to accommodate the disruption stemming from a new entrant with a disruptive business model, we analyze the differentiated efforts of four incumbent lodging firms to compete with the peer-to-peer lodging firm Airbnb. This study is the first to quantify the effects of innovation on incumbent tourism firms challenged by a disruptive entrant. It finds that adoption speeds, that is first vs. late adoption, make a difference as the former are awarded a significant increase in market value.