Home-sharing Platforms Research Articles

Bridging the Green Gap in Homesharing: How Platforms Can Increase Hosts’ Sustainability Intentions and Behavior

Homesharing platforms are under substantive pressure to become more environmentally sustainable. Key to this challenge is these platforms’ homesharing hosts, who have the opportunity to introduce new sustainability innovations (e.g., water-saving measures). However, knowledge of what drives hosts’ sustainability behavior is currently limited. We address this gap and investigate antecedents for hosts’ sustainability intentions. Our study is based on a survey in Europe (conducted in 12 languages), resulting in a sample of 1,392 hosts. Building on the theory of planned behavior, we perform three analyses: (a) quantitative and theory testing, (b) quantitative and explorative, and (c) qualitative and explorative. Notably, we find that attitude and norms, as well as financial resources and time, are the main drivers of hosts’ sustainability intentions. In addition, the presence of local service offices (i.e., a platform business model that internalizes service operations from hosts) moderates the effects of sustainability antecedents.

Economic impacts of digital home-sharing platform: Creative destruction in the hospitality industry

This paper describes an empirical study that was conducted by applying creative destruction theory to examine structural changes in the hospitality industry due to the growth of digital home-sharing platforms. To achieve these research aims, the current study considered the hospitality industry, which encompasses the accommodation and restaurant sectors, as well as Airbnb, representing the digital home-sharing platform. The findings revealed that there is a significant relationship between the exit of the accommodation industry and the supply of the digital home-sharing platform, while both entry and exit in the restaurant industry are significantly associated with the supply or performance of the digital home-sharing platform. Over time, this leads to industry transformations as certain segments of the lodging industry are replaced by digital home-sharing platforms, and as the restaurant industry undergoes a process of creative destruction, with establishments unable to adapt to changing business environments and the emergence of new facilities tailored to new technologies or accommodation models.

The moderating effects of Airbnb between urban conservation and housing rental market: A case study of Shanghai

The advent of peer-to-peer (P2P) home-sharing platforms such as Airbnb has noticeably impacted the housing rental market, as they have caused an increase in short-term rentals (STRs). Despite a growing body of research showing a positive correlation between Airbnb and housing rentals, the role of urban conservation efforts has received limited attention. In this study, we examine the moderating effects of Airbnb on the relationship between officially designated conservation zones and the housing rental market using data from township-level observations in Shanghai. The empirical evidence demonstrates that both the presence of historic conservation areas and the number of Airbnb listings have a considerable positive impact on property rental pricing. Furthermore, there is a direct correlation between the presence of more extensive conservation areas and an increase in house rental prices. Heterogeneity effects are evident in several townships in Shanghai with different levels of Airbnb activity, as the moderating effects are significant in townships with a large number of Airbnb listings. These results suggest that rising housing rents cannot be attributed entirely to the proliferation of STR services facilitated by home-sharing platforms. Future regulations for the housing rental market should address the impacts of home-sharing accommodations and the preservation and revitalization of designated conservation zones.

Noisebnb: An Empirical Analysis of Home-Sharing Platforms and Residential Noise Complaints

Practice and Policy-Based Abstract Externalities stemming from digital platforms have had a profound impact on the daily lives of people across the globe. In this work, we examine one such externality that contributes to urban quality of life, the noise stemming from home-sharing platforms, which has been subject to aggressive scrutiny by policymakers and the popular press but has received limited rigorous empirical attention. Against a backdrop of significant investment by municipalities to curb extant levels of urban noise, our findings suggest that these platforms are instead correlated with a decrease in noise complaints in New York City (notably when occupancy rates are lower or the residence is located near tourist attractions). These findings suggest that investments in abating the noise stemming from such short-term rentals are less necessary than indicated by anecdotal evidence and are better directed at other forms of urban noise sources, chiefly because such rental units are frequently unoccupied and therefore remain quieter than residential units. However, these findings also underscore the extent to which home-sharing networks may be further straining the already stressed housing market in large metropolitan areas like New York City.

Fulfilment of Expectations and Loyalty in Digital Home-sharing Platforms

Fulfilment of Expectations and Loyalty in Digital Home-sharing Platforms

Data sharing and tax enforcement: Evidence from short-term rentals in Denmark

Airbnb and other home-sharing platforms have been facing increasing regulation over the past years, mainly in the form of restricting short-term rentals through day caps. In contrast, as one of the first countries in the world, Denmark applied a collaborative strategy: In 2018, the government negotiated an agreement with Airbnb about the transmission of income data from the platform to the tax agency. We analyze how this data-sharing agreement affected hosts' behavior on the platform, using a difference-in-differences approach with Sweden as a counterfactual. We find that the agreement reduced hosts’ propensity to list property on the platform by 14%, while increasing listing prices by 11%. Our results indicate that platform exits were mostly limited to single-property hosts. In contrast, hosts with many properties and those in areas with initially low Airbnb penetration made their rental objects more often available and managed to increase the number of bookings. Overall, the findings imply that the data-sharing agreement not only helped to increase tax compliance but also led to a commercialization and spatial re-organization of short-term renting in Denmark.

The sharing economy and housing markets in selected European cities

A heated debate has emerged drawing a connection between housing affordability and home-sharing platforms such as Airbnb. Despite first regulatory efforts by municipalities, the impact on rents and house prices has been examined insufficiently in scientific literature, especially with regards to Europe. Therefore, this paper addresses this gap by analyzing data on Airbnb listings for 25 European cities between 2010 and 2019. Using fixed effects and dynamic panel regressions, we show that home-sharing has significantly contributed to a rise in rents and house prices in European cities. While these effects are mainly concentrated in city centers, we also document effects in other urban districts. Finally, recent home-sharing regulations are not associated significantly with housing affordability.

How privacy practices affect customer commitment in the sharing economy: A study of Airbnb through an institutional perspective

Privacy is an emerging issue for home-sharing platforms such as Airbnb. Home-sharing providers (business customers) are subject to both digital privacy risks (e.g., data breaches and unauthorized data access) and physical privacy risks (e.g., property damage and invasion of their personal space). Therefore, platforms need to strengthen their institutions of privacy management to protect the interests of providers and maintain their commitment. By applying the micro-level psychological aspect of institutional theory, our research investigates how providers decide their level of commitment to a platform by evaluating the institutions of the platform's privacy management. Our survey recruited 380 Airbnb providers from the Prolific panel. Structural equation modelling analysis shows that both physical and digital privacy practices strengthen providers' legitimacy judgement of the platform's privacy management and subsequently increase their commitment to the platform. Our theoretical contribution lies in revealing the effects of physical and digital privacy practices on B2B relationships from an institutional perspective. Our research is among the first to provide an integrative framework illustrating providers' psychological process of legitimacy judgement. It also has practical implications for sharing economy platforms to manage privacy.

Touristification, Airbnb and the tourism-led rent gap: Evidence from a revealed preference approach

Over the past decade, the global rise of home-sharing platforms, such as Airbnb, has catalysed the process of ‘touristification’ in major tourism cities. Touristification, a term recently used to describe tourism-induced gentrification, leads to a morphological transformation of a community into a tourism commodity. However, less is understood about the effects of this process, when it is triggered by short-term accommodation platforms, in reshaping urban housing markets. Therefore, in this case study, we apply the rent gap theory to the process of touristification and hypothesise that, ceteris paribus, (1) touristification can create a new potential ground rent that brings about a tourism-led rent gap (i.e., net positive externalities), whereas (2) in a low-density neighbourhood the urban conflicts caused by touristification can lead to a negative rent gap (i.e. net negative externalities). This study's instrumental evidence from the revealed preference approach confirms two opposing forces of the Airbnb listing density on house-type versus apartment-type accommodation rents. Further, its empirical findings imply that in framing policies for effective destination management, policymakers should consider the positive as well as the negative externalities associated with touristification.

The influence of customer trust and artificial intelligence on customer engagement and loyalty - The case of the home-sharing industry.

Trust is an essential factor in online and offline transactions. However, the role of customer trust has received limited attention in the home-sharing economy. Drawing on the revised stimulus organism response model and trust transfer theory, this paper examines how customer trust in home-sharing hosts and platforms affects customer relationships, manifested in customer engagement and loyalty. As artificial intelligence (AI) is extensively utilized within home-sharing platforms to facilitate business operations and enhance the customer experience, this study also examines the influence of AI on customer trust and other related outcomes. The research was undertaken in China, with respondents who had used home-sharing platforms. Results from structural equation modeling show that customer trust had a significant positive relationship with customer engagement and loyalty. Customer engagement mediates the relationship between trust and loyalty, while AI may have a negative moderating effect between host trust and customer engagement and customer engagement and loyalty. The paper contributes to marketing, sharing economy and AI research. The work has implications for practitioners offering suggestions to develop marketing strategies for business growth and sustainability.

Regulating Professional Players in Peer-to-Peer Markets: Evidence from Airbnb

We study professional players and their roles in peer-to-peer (P2P) markets. Most notably, P2P home-sharing platforms (e.g., Airbnb) consist of both professional hosts and nonprofessional individual hosts. What are the roles of the professionals? Should home-sharing platforms regulate their participation? Professional hosts may primarily offer properties that nonprofessional hosts would not supply and attract more guests—the differentiation effect. Or they may mostly supply similar properties and compete with the nonprofessionals—the competition effect. Using a unique data set of Airbnb listings, we first find that professional hosts’ properties are more expensive and have superior characteristics than nonprofessionals’. Second, we capitalize on a quasi-experiment in which Airbnb capped the number of properties a host can manage in several cities in the United States to determine the roles of professional hosts. With different predictions (about the policy impacts) under the differentiation versus competition effects, we find evidence suggesting the dominance of the latter. In particular, the policy increased the supply from nonprofessional hosts, and the price level of nonprofessional properties as a group went up after the policy. However, our findings of heterogeneity in policy impacts suggest that the dominance of competition is less prominent in certain markets. Finally, we find that the platform was not worse off in attracting reservations or securing revenue after the policy. Our findings contribute to both theory and practice as they reveal the roles of professional players and how P2P platforms can manage their participation. This paper was accepted by Kartik Hosanagar, information systems. Funding: K. Xie acknowledges financial support from the University of Denver’s Betty and Fritz Knoebel Faculty Fellowship [Grant #84383] and the Marketing Science Institute [Grant 4000791]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4480 .

Guest and Host Perspectives of Service Quality and Satisfaction in Digital Home-sharing Platforms

ABSTRACT Sharing economy accommodation services offered by companies such as Airbnb have become a very popular alternative to traditional hotels. However, existing research about service quality (SQ) in shared accommodation focuses only on the guest’s perspective. Given that hosts are an essential part of these services, this paper aims to identify the determinants of SQ for both guests and hosts. Based on an international survey (N = 501) the proposed dimensions are validated through an exploratory factor analysis and a confirmatory factor analysis. Then, structural equation modeling is applied to assess the impact of the SQ dimensions on overall guest and host satisfaction.

Housing Real Estate Economics and Finance

Housing research is one of the hot topics in many countries. This paper provides a quick review of the housing economics research in the US, Sweden, Latvia, China, Corsica, and Italy published in this special issue. Bao and Shah studied the effects of home-sharing platforms in general and the effects of the US’ Airbnb on neighbourhood rent. Wilhelmsson’s results showed that interest rates directly affected house prices and indirectly affected bank loans in Sweden. Caudill and Mixon threw light on the relative negotiating power of the buyer and seller as a key element of real estate price models. Čirjevskis presented a real application of “step-by-step” valuation options for real estate development projects as a managerial risk management tool for similar real estate development projects in the EU to make investment decisions during COVID-19 and in the post-COVID-19 era. Pelizza and Schenk-Hoppé used an exponential Ornstein–Uhlenbeck process to model price dynamics provincially and regionally to estimate the liquidation value.

Spatial Variability of the ‘Airbnb Effect’: A Spatially Explicit Analysis of Airbnb’s Impact on Housing Prices in Sydney

Over the last decade, the emergence and significant growth of home-sharing platforms, such as Airbnb, has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney—one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increase in Airbnb density is associated with approximately a 2% increase in property sales price. However, recognizing that Airbnb’s effect is geographically uneven and given the fragmented nature of Sydney’s housing market, we also employ a GWR to account for the spatial variation in Airbnb activity. The findings confirm that Airbnb’s influence on housing prices is varied across the city. Sydney’s northern beaches and parts of western Sydney experience a statistically significant value uplift attributable to Airbnb activity. However, traditional tourist locations focused around Sydney’s CBD and the eastern suburbs experience insignificant or negative property price impacts. The results highlight the need for policymakers to consider local Airbnb and housing market contexts when deciding the appropriate level and design of Airbnb regulation.

Dragging on multilisting: The reason why home-sharing platforms make long-term rental prices increase and how to fix it

• The presence of home-sharing platforms is believed to create externalities for the inhabitants of cities and touristic hotspots via gentrification and touristification processes, due mainly to the increase of long-term rental prices. • Despite existing externalities, home-sharing platforms can help property owners to monetize their assets and provide visitors with a higher value-added accommodation proposal than that of regular accommodation providers. • We posit and demonstrate, for the city of madrid (Spain), that the presence of home-sharing platforms is not responsible for the rise of long-term rental prices at the city level, but it is at the touristic hotspots (city center in this case) level. • We show that the effect found in touristic hotspots can be mainly attributed to the presence of home-sharing platforms, where multilistings (investors offering a great number of properties) play a significant role. • Public institutions need to regulate home-sharing platform activity, paying attention to where (touristic hotspots) and who (multilistings) is mainly responsible for the externalities. Regulations must protect (i) the economic freedom of individuals wishing to monetize their assets and (ii) the democratization of travelling as a leisure activity provided by the sharing economy. Airbnb is the largest accommodation provider in the world. Its activity has lowered the cost of travelling, while providing owners of properties with a better way to monetize their idle assets. However, controversy has arisen due to the externalities created by home-sharing platforms, namely gentrification and touristification, that reduce livability of spaces affected by their activity. We look into the effect of Airbnb on long-term rental prices in the city of Madrid in 2019. We use Multilayer Perceptron (MLP) to analyze the data. Our findings indicate that, at the city level, long-term rental prices are mainly impacted by the distance of the district to the city center. This factor overrides the importance of the number of properties offered in home-sharing platforms. This speaks of long-term rental prices at the city level being governed by complex processes, in which the presence of home-sharing platforms is not the dominant one. However, if we look closely at touristic hotspots, we find that the concentration of properties offered in home-sharing platforms and specifically the presence of multilistings affect long-term rental prices importantly. Based on our findings, we propose a tax framework to deal with the externalities caused by the disruption of home-sharing platforms.

The impact of photo verification service on sales performance in the peer-to-peer economy: Moderating role of customer uncertainty

The innovative service of photo verification is now offered by major home-sharing platforms. It remains unclear, however, whether and how a peer provider’s adoption of the platform’s photo verification service influences the provider’s sales performance. We draw on the theory of motivated information management to argue that verified photos are a crucial visual and experiential cue to reduce customer uncertainty regarding the properties and peer providers. We collect observational data from a leading home-sharing platform in China and utilize the propensity score matching method to account for endogeneity. Our results show that after adopting photo verification service, peer providers benefited from an improved sales performance in terms of revenue and rent days. The positive effect is stronger for properties with a source of greater uncertainty: (1) properties that lack certification and (2) properties with fewer customer reviews.

Optimal Pricing and Service Investment of Home-Sharing Platforms in a Duopoly Market

In this paper, we construct a fully covered duopoly market model. In this market, two home-sharing platforms provide differentiated rental services to consumers, respectively, and each platform has two strategies: short-term rental strategy and long-term rental strategy. This paper studies the pricing decisions and service investment of home-sharing platforms in a competitive market. The results show that, in the market equilibrium, how the platform chooses the strategy largely depends on the service quality of competitors. Specifically, when the difference in service quality is small, it is better for the two platforms to adopt the short-term rental strategy; otherwise, the two platforms are more inclined to adopt the long-term rental strategy. We also find that the commission rate and service cost will also affect the profitability of the platform. Finally, we extend the model to the uncovered market.

Airbnb and neighborhood crime: The incursion of tourists or the erosion of local social dynamics?

The proliferation of internet-based home-sharing platforms like Airbnb has raised heated debates, with many in the general public believing that the presence of Airbnb listings can lead to an increase in crime and disorder in residential neighborhoods. Despite the importance of this debate to residents, policymakers, and other stakeholders, few studies have examined the causal linkage between Airbnb listings and crime in neighborhoods. We conduct the first such empirical test in Boston neighborhoods, focusing on two potential mechanisms: (1) the inflow of tourists might generate or attract crime; and (2) the creation of transient properties undermines local social dynamics. Corresponding to these mechanisms, we examine whether the number of tourists (approximated with reviews) or the prevalence of listings predict more incidents of private conflict, social disorder, and violence both concurrently and in the following year. We find evidence that increases in Airbnb listings–but not reviews–led to more violence in neighborhoods in later years. This result supports the notion that the prevalence of Airbnb listings erodes the natural ability of a neighborhood to prevent crime, but does not support the interpretation that elevated numbers of tourists bring crime with them.

Mining Consumer Minds: Downstream Consequences of Host Motivations for Home-Sharing Platforms

AbstractThis research sheds light on consumer motivations for participating in the sharing economy and examines downstream consequences of the uncovered motivations. We use text-mining techniques to extract Airbnb hosts’ motivations from their responses to the question “why did you start hosting.” We find that hosts are driven not only by the monetary motivation “to earn cash” but also by intrinsic motivations such as “to share beauty” and “to meet people.” Using extensive transaction-level data, we find that hosts with intrinsic motivations post more property photos and write longer property descriptions, demonstrating greater engagement with the platform. Consequently, these hosts receive higher guest satisfaction ratings. Compared to hosts who want to earn cash, hosts motivated to meet people are more likely to keep hosting and to stay active on the platform, and hosts motivated to share beauty charge higher prices. As a result, these intrinsically motivated hosts have a higher customer lifetime value compared to those with a monetary motivation. We employ a multimethod approach including text mining, Bayesian latent attrition models, and lab experiments to derive these insights. Our research provides an easy-to-implement approach to uncovering consumer motivations in practice and highlights the consequential role of these motivations for firms.

Airbnb and Neighborhood Crime: The Incursion of Tourists or the Erosion of Local Social Dynamics?

The proliferation of internet-based home-sharing platforms like Airbnb has raised heated debates, with many in the general public believing that the presence of Airbnb can lead to an increase in crime and disorder in residential neighborhoods. Despite the importance of this debate to residents, policymakers, and other stakeholders, few studies have examined the causal linkage between Airbnb and crime in neighborhoods. We conduct the first such empirical test in Boston neighborhoods, focusing on two potential mechanisms: (1) the inflow of tourists might generate or attract crime; and (2) the creation of transient properties undermines local social dynamics. Corresponding to these mechanisms, we examine whether the number of tourists (approximated with reviews) or the prevalence of listings predict more incidents of private conflict, social disorder, and violence both concurrently and in the following year. We find evidence that increases in Airbnb listings--but not reviews--led to more violence in neighborhoods in later years. This supports the notion that the prevalence of Airbnb listings erodes the natural ability of a neighborhood to prevent crime, but does not support the interpretation that elevated numbers of tourists bring crime with them.