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The objective of this article is the bibliometric analysis of peer-reviewed literature for the crisis management strategy of sharing economy services during the COVID-19 pandemic. The examination of the use of data analytics to manage crises during COVID-19 and how sharing economy businesses utilized technology to forecast consumer behavior during this time, determine safe business practices, and enhance their operations were the essential observations of the research. The COVID-19 outbreak significantly impacted the sharing economy. Many businesses in this sector experienced declining sales as customers stayed home and were discouraged from sharing resources. Five case studies combined crisis management and data analytics-related keywords. After several keyword searches on the Web of Science (WoS) database, bibliographic coupling methodology with the assistance of VOSviewer computational software was the preferred method. The study emphasized important research fronts and factors directing the causality between analytical usage and sharing economy service operations. The research results also indicated that information forecasting is an essential part of crisis management with the creation of efficient strategies to navigate the current climate and set themselves up for long-term success by utilizing data to get insights into consumer behavior and market conditions. The study uses the modeling visualization tool Lucidchart and the bibliometric computation software VOSviewer. [ABSTRACT FROM AUTHOR]

This article examines real estate platforms and the data they generate to provide new insights into housing markets and practices, focusing on lower-cost and informal sectors, where building or rental regulations are often bypassed or contravened. We examine online listings advertised in Sydney, one of the most expensive cities in Australia and the world, compiling data from four dominant platforms – Realestate.com.au, Flatmates.com.au, Gumtree.com.au and Airbnb.com – each of which offers a particular type of rental accommodation. Using these datasets, we identify a typology of lower-cost and informal tenures and dwelling units, ranging from secondary dwellings and illegally subdivided apartments to shared accommodation and precarious rental agreements. Our study highlights a supplementary supply of rental housing, operating within the conventional private rental market, accessed and made visible via the platforms we examine. Applying a statistical regression approach, we examine relationships between concentrations of informal housing supply and socio-economic variables. The findings reveal intersections between digital platforms and evolving informal market practices and have implications for urban planning and housing policy. [ABSTRACT FROM AUTHOR]

Internet platforms enabling the short-term rental of private homes are an increasingly important provider of tourist accommodation and a challenge for urban policy. Airbnb is frequently blamed for encouraging property owners to remove their homes from the permanent housing market, thus contributing to the gentrification and displacement of local residents. Empirical research on this topic has been mostly represented by qualitative or indirect quantitative studies, which focus on changes in housing availability rather than the actual population. In our study, we fill this gap by presenting a study of the city of Stockholm, using two sources of georeferenced data: information on properties offered for rent on the Airbnb platform and micro-data on individuals and properties derived from the national statistical office. We verify whether the high number of apartment rental offers on the Airbnb website contributes to the high number of apartments that became uninhabited during 2012–2016. Using both aspatial and spatial autoregressive models, we find that the platform expansion does have a significant effect on the number of emptied apartments, and thus conclude that the presence of Airbnb contributes to the process of touristification, understood as the replacement of permanent residents with non-permanent populations. This confirms that when analysing urban population change and the gentrification process, mobile populations should be considered. Context-aware multiscalar and relational approaches are needed to understand the interrelation between human mobility, housing markets and regulations, and transnational internet platforms. [ABSTRACT FROM AUTHOR]

Digital and sharing platforms are transforming the business landscape and significantly impacting the global economy. This study provides a systematic review of the sharing economy (SE) in marketing and presents a future research agenda to advance the discipline. A comprehensive approach is utilized, incorporating bibliometric analysis, performance analysis, science mapping techniques, and topic modeling to analyze sharing economy research within marketing. The dataset comprises 325 articles on the sharing economy, from which eight key topics are identified: (1) analyzing customer ratings and sentiments, (2) understanding and evaluating customer experience, (3) customer orientation towards peer-to-peer accommodation services, (4) mapping customer relationships in the sharing economy, (5) analysis of user loyalty, (6) development of marketing strategies to enhance platforms, (7) identification of platform openness, and (8) actors within the digital platform ecosystem. By identifying research gaps, a future research model is proposed to comprehend the roles and influence of customers, peer service providers, and platform providers in the sharing economy. The findings of this study have practical implications for marketing practices within the SE. [ABSTRACT FROM AUTHOR]

This paper analyses the prediction capacity of machine learning techniques under severe demand shocks. Specifically, three methods – Naive Bayes, Random Forest and Support Vector Machine – are tested in predicting rental occupancy for tourist accommodation in the city of Madrid. We compare two different scenarios: firstly, the predictive capacity in the years prior to COVID-19 and, secondly, the ability to anticipate demand behaviour once the pandemic started. The results demonstrate first that without market disturbances, the Random Forest model exhibits the best predictive capability. Second, the COVID-19 pandemic caused such major changes that none of the three tested models are entirely reliable, although the Random Forest and Naive Bayes models outperform the SVM model. As a methodological novelty, this paper includes occupancy quantiles to resolve problems with available data and temporal biases. [ABSTRACT FROM AUTHOR]

This study addresses gaps in understanding accommodation satisfaction on Airbnb, focusing on Morocco as a representative of an important but unexplored region. It introduces guest count as a control variable and explores both linear and non-linear factors affecting satisfaction. Analyzing Airbnb reviews from 2013 to 2023, it emphasizes geographically-dependent determinants and variations in relevance based on host numbers. Non-linear links reveal overlooked factors, enhancing understanding beyond linear approaches. Accompanied by explanations, tables, and illustrations, the study aids Airbnb stakeholders in improving services. [ABSTRACT FROM AUTHOR]

Virtual travel experiences are increasing in various online platforms. In peer-to-peer platforms, people can even sell and buy virtual experiences (e.g., touring attractions virtually and personalizing trip itineraries). With a fresh theoretical lens of Touchpoints, Context, and Qualities of customer experience design, this study unpacks important attributes of virtual experiences in the sharing economy. Using a multi-method approach, this study identifies important attributes of virtual experiences and experience hosts using regression (Study 1) and conjoint (Study 2) analyses. As a result, the average rating of reviews about a virtual experience is the most important attribute, followed by the number of selling points, number of images, time length of the virtual experience, and the host's use of intuitive and plain words. The current study extends the customer experience design literature and provides implications of virtual experiences in the sharing economy to hospitality and tourism businesses. [ABSTRACT FROM AUTHOR]

Home sharing platforms have experienced a rapid growth over the last decade. Following negative publicity, many cities have started regulating the short-term rental market. Regulations often involve a cap on the number of days a property can be rented out on a short-term basis. We draw on rich data for short-term rentals on Airbnb and for the long-term rental market to examine the impact of short-term rental regulations with a day cap on various stakeholders: hosts, guests, the platform provider, and residents. Based on a difference-in-differences design, we document a sizable drop in Airbnb activity. Interestingly, not only targeted hosts (i.e., hosts with reservation days larger than the day cap), but also non-targeted hosts reduce their Airbnb activity. The reservation days of non-targeted hosts decrease between 26.27% and 51.89% depending on the treatment. Targeted hosts experience a similar decline. There is, nevertheless, significant non-compliance: more than one third of hosts do not comply with enacted short-term rental regulations. Additional analyses show that few properties are redirected from short-term rental to long-term rental use and that there is no significant drop in long-term rents. Drawing on a theoretical model, we tie the estimated effects to changes in stakeholders' welfare: Regulations significantly reduce the welfare of hosts, and the loss ranges between 46.30% and 9.02%. The welfare loss of the platform provider is proportional to the loss of the hosts. Welfare of guests decreases moderately ranging between 4.5% to 4.1%. The welfare of residents increases minimal. These results question the effectiveness and desirability of the studied short-term rental regulations. [ABSTRACT FROM AUTHOR]

Peer-to-peer accommodation has gained prominence in the sharing economy and e-commerce sectors, with big data playing a crucial role in understanding customer preferences and evaluating homestay satisfaction. This study proposes a novel methodology that integrates Natural Language Processing (NLP) techniques, a Random Forest model, and Geographic Information System (GIS) functionalities to quantify the complex relationship between homestay satisfaction and diverse customer preferences. Notably, this study addresses the positive bias inherent in listing scores by segmenting homestays into three categories (satisfactory, moderate, and dissatisfactory) based on sentiment analysis from online reviews. Furthermore, this study not only identifies eight key determinants of homestay satisfaction but also unveils the nonlinear relationships and interactions between them. More significantly, we identify specific threshold values for geographic determinants, offering actionable recommendations for homestay planning and layout. These findings provide valuable insights that can be leveraged to improve homestay experiences and promote the sustainable development of urban homestays. [ABSTRACT FROM AUTHOR]

Short-term rental (STR) platforms like Airbnb have significantly impacted urban housing sustainability, particularly in cities like New York City. The COVID-19 pandemic disrupted the STR market, raising questions about its resilience and effects on sustainable urban housing. This study addresses the following research questions: (1) How did unit and neighborhood characteristics influence the survival of Airbnb listings during the pandemic? (2) What changes occurred in the factors determining the emergence of new listings during the pandemic? Using data from Inside Airbnb, we applied Cox proportional hazard models and negative binomial regression to analyze changes before and after the pandemic. We found that during the pandemic, price discounts became crucial for listing survival, while traditional quality indicators like superhost status and high ratings lost significance. The importance of subway accessibility decreased, reflecting shifts in traveler preferences. Additionally, new listings were less likely to emerge in high-density Airbnb areas and more likely in neighborhoods with higher crime rates. These findings highlight the need for sustainable regulatory approaches that balance the benefits of STR platforms with protecting housing affordability and community well-being. Our study provides insights for policymakers aiming to promote sustainable urban housing during global crises. [ABSTRACT FROM AUTHOR]

The sharing economy (SE) is a nascent phenomenon representing a socio-economic process to optimise underutilised resources through digital platforms. This process facilitates the shared consumption of resources to maximise resource utilisation while supporting the circularity of resources. However, the successful operation of SE practices is hindered by the lack of identification of effective strategies for enhancing the SE implications, which are essential to comprehending SE practices and developing more sophisticated applications. Therefore, this research aims to provide the first insights into the strategies that enhance SE practices across diverse industries and identify knowledge gaps and future research directions. A systematic literature review (SLR) was conducted by selecting articles published in the 2014–2023 period in Scopus and Web of Science databases. Selected articles were subjected to descriptive and NVivo 14-supported thematic analyses. The descriptive analysis showed that, despite considering articles published in the last 10 years, all relevant articles were published in the last 5 years. Developed and developing countries showed almost equal contributions, while China was recognised as the country with the highest number of publications. Accommodation and transportation sectors were reported as the sectors with the highest number of publications. A cross-analysis was conducted to recognise the varying utilisation of different strategies across diverse industries and sectors. Ten different categories were identified through the thematic analysis that enhance SE practices: economic; environmental; geographic; governance; health, safety, and security; marketing; people; product/services; research, training, education; and technology-related strategies. Each category was discussed along with its relevant strategies, resulting in identifying a total of 84 strategies. These strategies were then presented alongside the responsible parties tasked with their implementation. The study contributes to the SE literature by providing an SLR for contemporary strategies utilised to enhance SE practices, specifically focusing on elucidating the most appropriate categorisation of these strategies. Moreover, this comprehensive SLR provides the first insights into the effective strategies that enhance SE practices across diverse industries. [ABSTRACT FROM AUTHOR]

Processes of responsibilisation aim to configure individuals into the governance models of digital platforms and realise versions of the sharing economy pursued by powerful platform owners. Questions are raised, however, as to whether this is an empowering process or one that puts participants at risk. Based on a qualitative study of Airbnb hosts in Europe, we explore their understanding of their own responsibilities as emerging hospitality practitioners. Our analysis shows that hosts actively engage in professional identity work and map a practice architecture which includes a set of responsibilities. We suggest, however, that this is not by itself a sign of empowered individuals rather a reaction to the perceived shift of Airbnb's strategy towards hotelisation of hosting practice. We contribute to an understanding of responsibilisation as a critical and reactionary process. [ABSTRACT FROM AUTHOR]

Following nearly a decade of unabated growth in the digitally disruptive short-term rental (STR) sector, the onset of the COVID-19 pandemic in 2020 caused a relatively abrupt two-year industry contraction characterised by substantial reductions in participating properties and booking activities. Given the sudden opportunity to rethink how STR markets fit alongside more traditional accommodation arrangements, this unanticipated Black Swan event catalysed much debate about the role that STRs play, and how they are regulated and managed. As the STR market rebounds toward a ‘new normal’, a timely opportunity exists to understand and theorise how and where the industry evolves. In this paper, we apply regression modelling and descriptive statistics to compare STR property utilisation across four regional markets in Australia both before and after the pandemic. We observe a sharp reduction yet strong intensification in available properties after the COVID-19 pandemic, with 27% fewer properties that were booked 26% more often across the nation. This was led by a significant geographical shift from capital cities to high-amenity, tourist-focused regions. Our findings suggest that this pivot is driven by spatial market segmentation, in which urban STRs are operated professionally, whereas regional markets are distinguished by their amenity value, both at the regional and property scales. Combined, the results of this study point to a more professionalised STR hosting landscape in which properties are more intensively used. Any potential policy reform should consider this evolution in the STR accommodation sector.

Abstract Peer-to-peer accommodation has gained prominence in the sharing economy and e-commerce sectors, with big data playing a crucial role in understanding customer preferences and evaluating homestay satisfaction. This study proposes a novel methodology that integrates Natural Language Processing (NLP) techniques, a Random Forest model, and Geographic Information System (GIS) functionalities to quantify the complex relationship between homestay satisfaction and diverse customer preferences. Notably, this study addresses the positive bias inherent in listing scores by segmenting homestays into three categories (satisfactory, moderate, and dissatisfactory) based on sentiment analysis from online reviews. Furthermore, this study not only identifies eight key determinants of homestay satisfaction but also unveils the nonlinear relationships and interactions between them. More significantly, we identify specific threshold values for geographic determinants, offering actionable recommendations for homestay planning and layout. These findings provide valuable insights that can be leveraged to improve homestay experiences and promote the sustainable development of urban homestays.

In a context of ever-growing demand for tourism property, this paper scrutinizes emerging forms of tourism-led housing commodification in Havana, Cuba. In 2011, the Cuban property market reopened to investment when the socialist government allowed the sale of private property at prices set in a market environment. We pay attention to the critical role of Cuban migrants, remittance investors and lifestyle elites in commodifying Havana’s historic housing stock and transforming residential property into short-term rentals, hotels, private restaurants and tourist boutiques. We demonstrate how the Cuban government has become an active market facilitator, either by restraining private competition or by encapsulating tourism property investment within broader channels of the state. We conclude that the case of Havana is indicative of broader trends in tourism and hospitality, particularly in the Global South and East. We propose tourism-led housing commodification as a conceptual framework for understanding these broader commonalities. [ABSTRACT FROM AUTHOR]

AbstractMost research on Airbnb focuses on the guests’ perspective or the effects of host-guest interaction. This paper explores the way professional and nonprofessional hosts develop relationship marketing with their guests. The results of 30 semi-structured interviews with Portuguese Airbnb hosts show the conscious importance of interactions with guests and customization to generate trust and increase guest satisfaction. The paper shows that the interactivity and functionalities of the Airbnb platform deepens the relationships between hosts and guests. Nonprofessional hosts are those who develop a closer relationship with guests, requiring guidance toward possible advanced electronic relationship marketing tools in the future. [ABSTRACT FROM AUTHOR]

The rapid proliferation of peer-to-peer short-term vacation rentals has sparked a debate regarding their impact on housing markets. This study further investigates this issue by examining the effect of Airbnb on relative rent costs in San Francisco. The research addresses a critical gap in understanding whether Airbnb financially burdens local renters within different income groups. The authors also differentiated the effect of Airbnb accommodations with different levels of commercialization by categorizing Airbnb listings based on their level of commercialization. Using the multiscale geographically weighted regression technique, this study also considered spatial variations in the relationship between short- and long-term rental markets. The findings indicate that the density of Airbnb only affects the relative rent of renters with a yearly household income between USD 50,000 and USD 75,000. Furthermore, the density of Airbnb listings from more commercialized hosts that own between three and eleven showed a positive relationship with the relative rent cost. This study highlighted the variability in the impact of Airbnb on the local community by income group, listing characteristic, and geographic region. This finding underscores the need for differentiated regulation toward peer-to-peer accommodations, as the impact on rent affordability varies by host commercialization level and renter income group. [ABSTRACT FROM AUTHOR]

The past decade has seen the growth of Short-Term Lets (STLs) through Airbnb and other platforms. Measuring the scale of this activity is challenging as platforms appear unwilling to share data. Most research on Airbnb uses data from commercial sources but this raises issues of equity in access and transparency. Open data exist, but geographic and temporal coverage is limited. We consider whether these open data can be used to study the STLs sector, using a city in Scotland. Using 2017 data to construct: (i) property-level estimates of income; and (ii) through comparisons with rents in the long-term rental market, an area-level vulnerability index to identify neighbourhoods at greatest risk of properties switching from long-term to short-term renting. This index is strongly associated with the growth of Airbnb listings over two years. We conclude that open data can provide a valuable basis for research and policy. We discuss strategies for improving knowledge about this sector including through new data collection. [ABSTRACT FROM AUTHOR]

Purpose: We challenge the conventional approach to distinguish between professional and non-professional Airbnb hosts by solely using the number of managed listings. Design/methodology/approach: We leverage the recently released platform policy that categorizes hosts' professionalism by their self-declared status. Our multinomial modeling approach predicts true host status, factoring in the number of managed listings and controlling for listing and host traits. We employ data from five major European cities collected through scraping the Airbnb webpage. Findings: Our research reveals that relying solely on the number of listings managed falls short of accurately predicting the host type, leading to difficulties in evaluating the platform's impact on the local housing market and reducing the effectiveness of policy intervention. Moreover, we advocate using more fine-grained measures to differentiate further between semi-professional and professional hosts who exhibit heterogeneous economic behaviors. Research limitations/implications: Reliable professionalism metrics are essential to curb unethical practices, promote market transparency and ensure a level playing field for all market participants. Originality/value: This work pioneers the revelation of the inadequacy of a commonly used measure for predicting host professionalism accurately. [ABSTRACT FROM AUTHOR]

In recent years, Airbnb has disrupted the accommodation industry, becoming both a valid alternative and a serious competitor to traditional accommodation. Understanding the consumer values associated with Airbnb and hotel accommodations is critical to comprehending travellers' preferences for the one or the other. This study illuminates the utilitarian and hedonic aspects of travellers' accommodation experiences with Airbnb and hotels and compares their roles and constitutions. We further examine which aspects elicit satisfaction and dissatisfaction, uncovering the qualities and weaknesses of the accommodation types. Using text-mining methods (STM, sentiment analysis), we analysed 437,820 web-scraped reviews from travellers who stayed at an Airbnb or a hotel via Booking.com in Prague, Czechia. We found that hedonic values -- the host, neighbourhood ambiance, enjoyment, and homeliness -- are the distinguishing aspects of Airbnb experiences, while utilitarian categories associated with convenience -- room comfort, food and drink, and cost-effectiveness -- distinguish hotel experiences. We further found that the key quality of one form of accommodation is simultaneously the main weakness of the other: in hotels, the main source of satisfaction is the room, and the main dissatisfying aspect the staff, while in Airbnb, the host elicits only positive sentiments, and the room is the main source of dissatisfaction. We also revealed a substantive common base of the experiences. Practical and theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

This study examines the interplay between Airbnb and gentrification in Thessaloniki and Greece, focusing on their economic and social impacts on urban neighborhoods. Utilizing data from 110 online publications and qualitative insights from ten semi-structured interviews with real estate agents, Airbnb stakeholders, residents, and experts, the research provides a nuanced view of these dynamics. The findings suggest that Airbnb influences housing markets by driving up rental and home prices, potentially exacerbating housing scarcity and displacing vulnerable populations in gentrifying areas. While this aligns with the existing literature, the results remain tentative due to the complexities involved. The trend toward corporate-hosted short-term rentals appears to shift Airbnb away from its original community-focused model, though this shift is still evolving. The COVID-19 pandemic introduced changes, such as a move from short-term to long-term rentals and the conversion of commercial spaces to residential use, impacting neighborhood dynamics. However, these effects may be temporary and do not fully address broader housing issues. While an oversupply of Airbnb accommodations might stabilize rental prices to some extent, its impact on the overall housing crisis remains uncertain. Future research should investigate the long-term effects on housing affordability and social equity, considering the limitations of current findings. [ABSTRACT FROM AUTHOR]

In literature, several researchers have discovered that the reviews written about Airbnb accommodation tend to be extremely positive than those published on other famous platforms, consequently, many negative experiences remain untracked. Leaving negative experiences underrepresented hampers hosts' ability to improve their services. To overcome this gap, we employ Small Area Estimation to quantify negative sentiment in Airbnb reviews and the relative critical topics that characterize them. Our methodology involves a two-step process: first, we employ sentiment analysis and topic modeling to identify negative sentiment and critical issues, followed by the application of a mixed effect random forest model to provide a granular analysis of Airbnb reviews in small sub-populations in the context of small area estimation. We focus on domains of the city of Rome defined by geographical areas and the presence of hosts and Superhosts. Our findings reveal nuanced sentiment variations and critical topic proportions that traditional methods often overlook. [ABSTRACT FROM AUTHOR]

Researchers have yet to examine emotional solidarity (ES) shared between residents and peer-to-peer accommodation (P2PA) hosts. Data collected from a survey of 325 residents in Savannah, GA shows ES to have a direct effect on the perceptions of the positive and negative impacts of P2PAs and that ES's influence on support for ES is mediated through these perceived impacts. This suggests the importance of having P2PA hosts living in the community where residents can get to know them and understand the importance of the P2PA to the host's income and quality of life. [ABSTRACT FROM AUTHOR]

Airbnb has created a significant incentive to invest in real-estate with the purpose of short-term accommodation provision in touristic cities. The robust growth of Airbnb supply has been accompanied with an increasing professionalization of the platform, contributing to such challenges as overtourism and gentrification. The main aim of this analysis is to examine the spatial characteristics of Airbnb supply in Barcelona, Berlin and London, focussing on the differences between offers that belong to non-professional and professional hosts. Based on Exploratory Spatial Data Analysis techniques the study demonstrates that listings that belong to professional hosts are more concentrated in city centres, and are more influenced by the location of tourist attractions and hotels than non-professional offers. On the other hand, non-professional listings facilitate a spatially more diverse accommodation supply. The results suggest that professional offers may contribute more to the negative effects of Airbnb on local residents. [ABSTRACT FROM AUTHOR]

This study examines the information diffusion of "Airbnb discrimination" and related digital activism on Twitter. The model-based inferential network analysis shows a hub-and-spoke network that is loosely connected, indicating that the diffusion network of Airbnb discrimination includes various issues (e.g., antisemitism). The retweet network mirrors the existing offline relationship of users (e.g., those who support opinion leaders of antisemitism), demonstrating a core–periphery structure during the information diffusion process. This study not only empirically tested the retweet relationships but also provided theoretical explanations on how these relationships form through the notion of curative logic and two step information flow theory. The findings of this research challenge the widely accepted assumption about social media that "the more users share, the more people will see." [ABSTRACT FROM AUTHOR]

The rapid spread of the new coronavirus (COVID-19) around the world since early 2020 has caused significant economic, social, psychological, and public health costs. The COVID-19 pandemic hit almost all economic sectors including the hospitality and tourism industry. This review paper examined the impacts of COVID-19 on short-term housing and the factors influencing these impacts. The existing literature reported generally negative effects of COVID-19 on the operating performance of the short-term accommodation industry. COVID-19 impacted on travellers' perceptions, host-guest interactions and psychological well-being when choosing short-term accommodation. This review also provides implications for minimising the impacts of COVID-19 or similar future disruptive events on short-term accommodation operations and surviving the crisis in the short-term accommodation sector. [ABSTRACT FROM AUTHOR]

In the competitive landscape of Airbnb hosting, optimizing pricing strategies for properties is a complex challenge that requires revenue maximization with high occupancy rates. This research aimed to introduce a solution that leverages big data and machine learning techniques to help hosts improve their property's market performance. Our primary goal was to introduce a solution that can augment property owners' understanding of their property's market value within their urban context, thereby optimizing both the utilization and profitability of their listings. We employed a multi-faceted approach with diverse models, including support vector regression, XGBoost, and neural networks, to analyze the influence of factors such as location, host attributes, and guest reviews on a listing's financial performance. To further refine our predictive models, we integrated natural language processing techniques for in-depth listing review analysis, focusing on term frequency-inverse document frequency (TF-IDF), bag-of-words, and aspect-based sentiment analysis. Integrating such techniques allowed for in-depth listing review analysis, providing nuanced insights into guest preferences and satisfaction. Our findings demonstrated that AirBnB hosts can effectively utilize both state-of-the-art and traditional machine learning algorithms to better understand customer needs and preferences, more accurately assess their listings' market value, and focus on the importance of dynamic pricing strategies. By adopting this data-driven approach, hosts can achieve a balance between maintaining competitive pricing and ensuring high occupancy rates. This method not only enhances revenue potential but also contributes to improved guest satisfaction and the growing field of data-driven decisions in the sharing economy, specially tailored to the challenges of short-term rentals. [ABSTRACT FROM AUTHOR]

The concept of women empowerment has not been extensively examined within P2P accommodation. This study investigates female Airbnb hosts’ empowerment gained through hosting on the platform. Additionally, the study examines the impact of their empowerment on their quality of life. The study applied Structural Equation Modelling to a sample of 343 female Airbnb hosts established in Greece. Findings reveal that female hosts are empowered differently in terms of the dimensions of empowerment (economic, political, social, psychological and educational) according to their hosting motives and proactive attitudes. Findings indicate that empowerment through hosting positively affects female hosts’ quality of life, whereas former experience in tourism moderates their empowerment. Important theoretical and practical implications are elicited regarding gender equality in hospitality. [ABSTRACT FROM AUTHOR]

Despite the growing number of studies on women empowerment in tourism, the topic has received scant attention in the expanding sector of peer-to-peer (P2P) accommodation. This paper sets out to explore the perceptions of female Airbnb hosts regarding the ways in which hosting on the platform contributes to their empowerment. Semi-structured interviews with 30 female hosts located in Greece were undertaken, using purposive sampling. Study findings reveal that women empowerment through hosting is achieved varyingly by female hosts, with several factors influencing the process. A framework of women empowerment through hosting is provided to illustrate the conditions, process and outcomes of women empowerment through hosting. Study findings provide significant theoretical insights which may serve as a point of departure for further research into this under-researched topic. Findings also make a practical contribution as they enable policymakers and industry practitioners to improve gender equality, which is essential for sustainable development. [ABSTRACT FROM AUTHOR]

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Many tourism studies leverage the hedonic price model to gauge tourists' willingness to pay for diverse attributes of short-term rental properties. However, when this estimation is applied to the temporal analysis, it can be biased if variables varying with time, such as term structure effects in short-term rentals, are omitted. This paper introduces a repeat sales Airbnb ADR (average daily rate) index to track the change in quality-adjusted rentals of Airbnb properties over time in Auckland, New Zealand, while factoring in the term structure. The findings confirm that using repeat sales data from Airbnb listings can significantly mitigate the bias linked to time-varying attributes. Results demonstrate that when the term structure is not considered, the ADR calculated by the hedonic method may be overestimated by 0.2% per day of the tenancy term. The inventive Airbnb ADR repeat sales index enables the assessment of Airbnb rental trends, taking into account changes in the term structure of leases. This new index can potentially enhance Airbnb listings by incorporating the effects of lease term structures. [ABSTRACT FROM AUTHOR]

Underpinned by the Experience Economy framework, this study investigates the increasingly popular online peer-to-peer tourism experience and its impacts on participants' post-experience recommendations. Using Airbnb Online Experiences reviews, a mixed method design including text-mining, sentiment analysis, and regression was performed. Findings show that participants' sentiments toward educational, escapist, and entertainment aspects positively influence their recommendations. Their positive experiences with hosts enhance the positive relationship between participants' educational experiences and recommendations. This study contributes to extant tourism literature by empirically developing a detailed and comprehensive perspective of the emerging peer-to-peer online experiences in tourism. [ABSTRACT FROM AUTHOR]

This study aims to measure and analyze the satisfaction of Turkish customers with their use of the sharing economy, using the case of the accommodation via Airbnb. Based on the positive and negative points that consumers find important in the formation of satisfaction and repurchase intention, this study aims to provide output for the sharing economy applications in terms of business models and communication channels that they need to improve. This study was designed as a quantitative study and its population consists of Airbnb users. 395 people were reached with the convenience sampling technique and the data was obtained with a survey form. IBM SPSS 26 program was used to analyze the data and findings were interpreted. According to the results of the study, the most important concept for satisfaction was found as reliability. Reliability was followed by price and service quality, respectively. It was found that fashion conformity, belonging to the community, and environmental impact has no statistically significant effect on satisfaction. [ABSTRACT FROM AUTHOR]

An underdeveloped theme in scholars' understanding of the personal services sector of the platform economy—also known as the "sharing economy"—is change. Most research on ride-hail, food delivery, accommodations, and other personal services has offered largely essentialist accounts. In this paper, we focus on how platforms have become increasingly "commercialized." In labor-intensive services, commercialization occurs as a growing fraction of the work is done by a core of full-time, dedicated workers. However, platforms that rely primarily on capital may display similar dynamics, in which a small number of participants account for the majority of activity and capture the largest share of value. In this paper, we present the first comprehensive account of commercialization of a major platform. We analyze how Airbnb markets in the 10 largest short-term rental markets in the United States changed between 2015 and 2019. We find considerable evidence of commercialization, as a rising majority of properties are rented on a very frequent basis, and casual listings, while still present, are a small and falling percentage. Relying on an original database of regulations, we show that enactment of even the strictest regulations has not durably reduced the number of listings and has had limited success in altering the mix of commercialized and casual listings over this period. We also consider the impact of COVID-19 on this platform and the sharing sector. We conclude that the short-term rental market on Airbnb has become a fairly conventional one, with little of the peer-to-peer character of its earlier days. [ABSTRACT FROM AUTHOR]

The purpose of the study is to highlight the important amenities listing variables and the pervasiveness of the determinants to the "superhost" status in the online shared destination accommodation of the tourism and hospitality market. The potential guests consider the superhost status as a quality indicator of the Airbnb accommodation and promise of the host for their offered amenities and thus increasing their rental demands resulting in more revenue from more bookings. Using the Airbnb listing dataset of four cities of Canada and eleven cities of the United States, the study applied six different data mining techniques to find the importance of listing variables. It identified essential amenities based on their presence among the top variables in the applied models. The findings of the study were the identification of a reduced set of offered amenities and service variables that influence Airbnb's reward of the "superhost" badge as a visual symbol of trust and credibility. Thus, the findings help to develop better service quality for tourists and at the same time helps to mitigate the complexities confronted by hosts with multiple listings. [ABSTRACT FROM AUTHOR]

The Airbnb business plays a significant role in connecting visitors to the local community and promoting the protection of the local environment. However, little research has focused on the proenvironmental behaviors (PEBs) of Airbnb guests. This study aims to investigate the differences in PEBs between hotel guests and Airbnb guests by examining a conceptual model that incorporates place attachment, environmental concern, and PEBs. An online survey involving 254 hotel guests and 259 Airbnb guests was conducted. The findings revealed that place attachment significantly predicted visitors' environmental concern and PEBs. The results of the mediation analysis further demonstrated that environmental concern played a significant role as a mediator between place attachment and PEBs. Additionally, the invariance test indicated that place dependence had a stronger impact on environmental concerns among Airbnb guests than hotel guests. These findings highlight the distinct roles of place attachment dimensions in shaping PEBs between the two groups. [ABSTRACT FROM AUTHOR]

Airbnb is a platform allowing peer-to-peer accommodation options for people sharing their own extra space. Though it sounds like a simple method of sharing and exchanging values in a sharing economy, however, there are many challenges behind its implementation. It is crucial to look at both sides of the coin to understand not only what it brings but what it causes as well. Airbnb is a comparatively new phenomenon in modern times and changes traditional tourist behaviour as well as the accommodation situation in the market. It is a big part of the sharing economy and brings a range of socioeconomic advantages and disadvantages to stakeholders. It is assumed as a sustainable, multi-stakeholder beneficial form of accommodation service provision and contributes to inclusive destination development. However, the uncontrollable utilisation of residents' spare spaces also leads to concerns related to social disturbance, and erosion of neighbourhood social capital. This qualitative research uses semi-structured interviews to collect the primary data from providers of Airbnb spaces and the local non-commercial residents of that geographical area in Central Prague. The findings compare the perspectives of providers and residents and provide useful insights related to opportunities and concerns for the stakeholders related to social disturbance due to this disruptive innovation. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to investigate the role of the service provider in determining customer satisfaction in sharing economy services. The authors sought to examine how the intrinsic and extrinsic cues along with their interactions influence customer satisfaction. Design/methodology/approach: This research uses a mixed-methods design to test the hypotheses. Study 1 uses secondary data from Inside Airbnb. Study 2 uses a 2 × 2 × 2 between-subject experimental design. Findings: Both studies support the confirmation bias perspective over the expectancy-confirmation perspective in explaining the interplay among different cues in determining customer satisfaction. In the context of Airbnb, in the absence of a Superhost badge, if hosts adopt a reactive communication style, physical presence has a greater impact on customer satisfaction compared to virtual presence. Originality/value: This study extends the services marketing literature and cue utilization theory by investigating the dynamic interactions among multiple intrinsic and extrinsic service cues. It shed new light on how a combination of these cues may become additive or redundant in determining customer satisfaction. This study contributes to the services marketing literature by addressing the interactive nature of sharing economy services and the neglected role of service providers. [ABSTRACT FROM AUTHOR]

This study investigates trust dynamics in sharing economy services during the COVID‐19 crisis, comparing Airbnb and Uber as prominent representatives of accommodation and transportation services in tourism. Guided by two research questions, the study first explores the antecedents and mechanisms of trust creation on these platforms and then examines how the global pandemic affected trust in these services. The findings reveal that structural assurance, privacy protection, and social influence (only for Uber) are key antecedents of trust. Trust, in turn, significantly influences perceived usefulness and the intention to use both platforms. The results also show that perceived risk, heightened by COVID‐19 concerns, negatively moderates the relationship between trust and usage intention. Comparing the two platforms, Airbnb exhibited higher levels of structural assurance, perceived usefulness, social influence, and usage intentions than Uber. Theoretically, this study advances knowledge by integrating technology acceptance literature with trust‐focused insights from tourism research. Practically, the findings guide sharing economy platforms in enhancing user trust and intention, particularly during crises. [ABSTRACT FROM AUTHOR]

This paper examines the physical limits but paradoxically symbolic expansion of the Airbnb model beyond the the touristified historical center of Madrid. We move to the margins of the city and analyzed every host ad and guest comment in the Villaverde district, characterized as a former industrial working-class neighborhood also welcoming various waves of immigrants. Our results reveal a novel figure in the platform model, which we have characterized as the "peripheral host," who attempts to participate in this business model based on two strategies: first, by constructing an imaginary "digital tourism space" that inserts the periphery into the tourist city; and second, by "platforming host practices" through the provision of a "personalized guest experience" and on-demand tasks. In our study, we propose an explanatory model that sheds light on the ways in which platform urbanism is transforming work, culture and urban society beyond city center. [ABSTRACT FROM AUTHOR]

The rapid growth of short-term rentals (STRs) is leading researchers to frame these urban transformations indifferently as gentrification, touristification or tourism gentrification. This paper proposes that these concepts, though closely related, are not best suited to explain the urban transformations created by STRs. Using a theoretical and empirical approach, it attempts to delve into this theoretical debate. Since housing assetization is what ultimately drives the process, STRs should be framed as a specific form of housing assetization. It is suggested that the term that best captures this urban accumulation strategy and has greater explanatory power is that of STR housing assetization. The aim of this paper is twofold. Firstly, to theoretically justify the suitability of the STR housing assetization concept and specify its particularities as an urban accumulation strategy. Secondly, this accumulation strategy can be empirically observed by analyzing how STR markets develop in particular cities. For this purpose, the Spanish city of Valencia has been chosen. [ABSTRACT FROM AUTHOR]

Since its appearance 12 years ago, the digital platform Airbnb has revolutionized the temporary accommodation system worldwide, leading to diverse territorial impacts beyond the tourism and hospitality industries. Despite its distinct presence in Latin America, there is no review of the existing academic literature in the region to date. Against this backdrop, the purpose of the article is to develop a literature review of Airbnb in Latin America from the critical perspective of urban studies. To do so, exploratory-descriptive research was carried out based on the review of scientific publications that addressed the topic of Airbnb, up to and including 2020, in four international academic journal databases: Scopus, Dialnet, Scielo and Redalyc. The main results show that the existing literature on Airbnb in urban studies in Latin America is still at an early stage, with little development compared to that of other world regions, where the tourism and business model approaches seem to occlude other facets of the phenomenon. These results made it possible to outline a future research agenda on temporary accommodation in the region. [ABSTRACT FROM AUTHOR]

Online consumer reviews (OCRs) are characteristic of, and play a vital role in, the sharing economy, the new business model for (in particular younger) generations of consumers. Even so, discussions of the pragmatic strategies that sharing businesses employ in response to negative OCRs are still a scarcity in academic literature. The present article makes an original contribution to rapport management studies by examining both the negative and positive rapport management strategies (RMS; Spencer-Oatey 2008) in the responses of British and Chinese Airbnb hosts to 200 negative OCRs in English and 200 negative OCRs in Chinese; among the 400 responses by Airbnb hosts replying to their angry guests' negative OCRs, there were just 10 negative and 10 positive RMSs. The study also examines similarities and differences between English and Chinese responses to negative OCRs. [ABSTRACT FROM AUTHOR]

Collaborative consumption has generated the appearance of new business models, such as those created by peer-to-peer platforms, such as AirBnB, focused on renting the accommodation of the users themselves to other users. The growing popularity of AirBnB has resulted in an emerging body of literature examining the factors that drive or deter consumers from choosing AirBnB (Sakr et al., 2024;). This work is based on a sample of 405 travellers who regularly use AirBnB to book accommodation on their journeys. They are asked about about their different motivations toward use of this type of reservation (e.g. hedonic, environmental sustainability, economic benefit, convenience, etc.), user personality values (i.e. individualism-collectivism; communal-exchange relationships), engagement with the AirBnB brand, and some personal characteristics (e.g. gender, age, education, economic situation, etc). A latent segmentation -through Latent Gold® software- was developed to obtain different profiles of AirBnB users based on above variables. Preliminary results show quite heterogeneity in the motivations and effects on the indicated dimensions. This helps to segment the users and detect different profiles with different motivational connections with the personal characteristics of users, engagement with this platform and their communal orientation about this type of sharing tourism. This motivational and physiological heterogeneity can make it easier for people to be reached through different communication strategies and arguments both by the tourism sector’s businesses and by public agencies with interests in city tourism management.

This study investigates the impact of Airbnb announcements on hotel stock prices across ten countries, distinguishing between exact- and general-location announcements. We found that while general announcements have minimal impact, those with exact locations consistently reduce hotel stock prices, as evidenced by negative cumulative abnormal returns (CAR) trends. The primary impact occurs within the [−3, +1]-day window surrounding the announcement. These robust findings persist across various tests, underscoring their reliability. Implications include the importance of investor awareness regarding location-specific announcements and the need for regulatory examination of information disclosure practices on platforms like Airbnb., n.d. The study offers valuable insights for investors and policymakers navigating the dynamic landscape of the hospitality industry in the age of online platforms.