Airbnb Host Research Articles

Social Responsibility and Airbnb Hosts: Voices from Northern Cyprus

This study examined relevant linkages between motivational factors to be the owner of P2P accommodation (Airbnb host) and being active in pro-environmental and pro-social actions in life practices using a qualitative research method. Our study contributes to the literature associating the motivations of being an Airbnb host and being active in sustainability issues under the framework of moral values. Furthermore, the study analyzed whether an individual awareness of sustainability practices by Airbnb hosts influences their motivations for social responsibility actions in their hosting practices. The key themes followed were ‘Community Engagement and Pro-Social Practices’, ‘Environmental Consciousness and Pro-environmental Practices’, ‘Family Values on Moral Identity and Legal Compliance’, and ‘Restoration and Cultural Heritage’. Findings revealed that hosts stress the importance of the level of environmental consciousness that is gained from education in fostering social responsibility. Respondents believed that teaching cultural heritage, environmental awareness, and ethical values, especially to children, is crucial to building a responsible society. Additionally, participants expressed a sense of social responsibility through the restoration of idle and old houses, contributing to the preservation of cultural heritage and historical structures. As a context of the moral identity issue of respondent hosts, the influence of family values on the development of moral identity was highlighted. The findings of the study showed that hosts work in a team to implement necessary projects for the benefit of society. The study ends with a discussion of the findings and relevant suggestions for the industry.

Exploring the strategic role of Marketer-Generated-Content analytics towards Airbnb hosts sales optimization

ABSTRACT Although user-generated content is reported to improve Airbnb host’s sales, the impact of Marketer-Generated Content (MGC) on the minimum sales generated from the reviewers who have reviewed the MGC is yet to be explored. This study examines MGC of title descriptions analysis from the City of Los Angeles listing data to understand their importance in predicting hosts’ net sales. The analysis employs two complementary econometric approaches: parametric multiple regression and the non-parametric multivariate adaptive regression spline model across three neighbourhood groups and two price groups. The findings indicate hosts can employ MGC to optimize sales and should highlight feature words in the title that best reflect the property characteristics and appeal to a target group that may be location-specific, price-sensitive, or both. The title should be informative and detailed within a limit of 10 words. The novelty of the work is to identify the influence of total sales for respective feature words from the title description of Airbnb property and to analyze their uses in marketing communications. The practical implications indicate that host-generated feature words are crucial in maximizing net sales for the property.

To be honest or positive? The effect of Airbnb host description on consumer behavior

On accommodation-sharing platform, host self-description influence consumer behavior as an important information. Based on the Perceived Value Theory and the Expectation Confirmation Theory, we developed an analytical framework to investigate the relationship between host description strategies and consumer behavior of room booking and satisfaction. We measured host description strategies (honest description and positive description) using machine learning and rule-based text analysis methods. Then we verified the different effects of two host description strategies on each of consumer behaviors based on a panel dataset from Airbnb. Positive description and honest description have a positive impact on room booking and consumer satisfaction respectively. Room price moderates the relationship between host descriptions and consumer behaviors. A highly positive description strategy can promote bookings for high-priced listings but decrease satisfaction. The honest description strategy has a positive effect on the bookings of low-priced listings. This study contributes to tourism literature and property hosts in practice.

Professionalisation and performance of Airbnb hosts in rural regions

This paper explores the professionalisation and performance aspects of Airbnb hosts in rural regions in Denmark, Iceland, and Norway. More specifically, based upon the professionalisation of hosts, which represents a proxy for the scale of their entrepreneurial engagement, the host landscape in the rural regions is investigated, resulting in different host profiles, including individual single- and multiple-listing hosts, and small and large tourism companies. The paper subsequently estimates the service quality performance of Airbnb hosts in relation to their professionalisation in rural regions through a u-shaped relationship, with the professionalisation influencing the performance evaluation of the hosts by the users. This twofold empirical analysis amends the extant literature, as it provides both a more nuanced and more comprehensive description of the nature and scale of Airbnb host engagement in rural regions, and points to the vast entrepreneurial opportunities for private households and companies on the platform.

The Influence of Linguistic Styles in Property Titles on Room Rates: A Hedonic Pricing Model

Consumers are drawn to the inherent quality of a product or service and how it is portrayed and described. This study investigated the impact of language used in property titles on pricing strategies and financial performance in peer-to-peer (P2P) accommodations by adopting the Language Expectancy Theory (LET) as a theoretical framework. The findings of this study demonstrate the significance of linguistic styles in property titles for determining P2P room rates, rental volume, and overall performance. Property titles that exhibit formal, logical, and hierarchical thinking are perceived as more sincere, personalized, and informative, resulting in higher rates, more significant rental volumes, and improved overall performance. On the contrary, properties with titles that convey expertise, and confidence, or adopt a positive and upbeat style tend to put lower room rates and yield lower performance yet generate higher volumes. This study expands the application of LET to P2P communication between an Airbnb host and a potential guest.

Impact of Airbnb Host Profile Photos on Guest Star Ratings Based on Cultural Differences in China and the United States

This research analyzed the profile photos and star ratings of 45,000 Airbnb hosts in China and the United States, investigating cultural differences in host and guest behavior. The results indicated the existence of cultural differences in the degree of facial disclosure and in facial expressions and their influence on guest ratings. More specifically, first, fewer hosts in China revealed their faces in profile photos than hosts in the United States. Second, in China, star ratings given by guests to hosts who did not disclose their faces were lower than to hosts who did disclose their faces, but in the United States, there was an even greater reduction in ratings for hosts who did not disclose their faces. Third, the facial expressions of hosts in China did not look as happy as those in the United States. Fourth, happy facial expressions of hosts had a more positive impact on guest ratings in China than in the United States. These findings highlight the importance of using profile photos showing happy facial expressions and this is especially important in China.

Self-disclosure and trust in the shared economy: a cross-cultural comparison

Airbnb is one of the fastest-growing businesses within the sharing economy. In this online marketplace, hosts can list their spare rooms, apartments, or houses as accommodation for Airbnb guests in return for money. Since customers tend to be careful when booking a stranger's house, trust is one of the most important elements of Airbnb. One concrete way of establishing trust is self-disclosure. This study explored online marketplaces such as Airbnb and their users with a framework on how self-disclosure in personal descriptions can be used to increase booking intention. An online experimental survey with two conditions was conducted (implicit vs. explicit host self-disclosure). There were 129 Dutch participants and 71 Chinese participants from China. Contrary to our expectations, implicit language in self-disclosure by the Airbnb host led to more trust than explicit language. Airbnb guests from the Netherlands had higher booking intentions and more trust in the Airbnb host after reading an implicit self-disclosure compared to guests from China. These cultural differences disappeared with the explicit self-disclosure profile.

에어비앤비(Airbnb) 숙소의 가격결정 요인분석: 부산광역시를 중심으로

The purpose of study is to analyze price determinants of Airbnb pricing in Busan and present political implications. Samples are Airbnb accommodations in Busan during the month of May in 2022. In total, 188 accommodations were collected and analyzed by Hedonic price model. To improve the robustness of regression, 3 models are used. Rating, number of bathroom, maximum capacity, Superhost dummy, Beach dummy, South dummy are significant for all models. The consequence of this research is presented as follows: high-rated accommodations that are hosted by super host claim higher price; being located near beach and tourist attractions increase prices. Airbnb accommodations with more capacity and bathrooms require higher pricing. Especially, bathrooms have bigger impact than capacity because it’s hard to be manipulated. This result can be a guideline not only for Airbnb host but for hotelier in managing accommodation. It turns out that tourists who visit Busan are willing to pay higher price for staying in coastal tourist city. Seoul and Jeju have same consequence, however their impact was much smaller compared to Busan. Though luxury demand can be the reason, the extent of it is too much. Thus, Busan needs to raise another tourist attractions to be dispersed.

More popular, more listings? Effects of popularity on Airbnb host expansion

PurposeSharing accommodation has lowered the threshold for digital entrepreneurship in the accommodation industry, prompting entrepreneurs to join this industry. However, digital micro-entrepreneurs have been ignored by previous studies. To bridge the gap, this study aims to explore the impact of reputational asset (host popularity) and host’s human capital (entrepreneurial entry speed and managerial seniority) on host expansion grounded on the resource-based theory.Design/methodology/approachThis study obtained crawler data by python from Airbnb.com, locking the time range to the past five years from 2013 to 2018 in Beijing of China. This study finally has 348 hosts’ balanced panel data to estimate the ordinary least squares regression model with fixed-year effect.FindingsResults demonstrate that host popularity has a significant positive effect on host expansion. Furthermore, entrepreneurial entry speed strengthens the positive effect of host popularity on host expansion, whereas managerial seniority weakens the positive effect. The three-way interaction analysis reveals that the positive impact of host popularity on host expansion is strongest when managerial seniority is smaller and entrepreneurial entry speed is faster.Research limitations/implicationsThe research has important implications to how the platforms interfere with the implementation of host expansion strategy and adds valuable insights to understand the transformation process of host expansion from nonprofessional to professional.Originality/valueThe research has expanded the literature related to the micro-entrepreneurship of the sharing economy and verified the application of resource-based theory under sharing economy.

Technological innovations and preexisting markets: The interaction between Airbnb and New York’s hotel and housing markets

AbstractThis paper analyzes the interaction between Airbnb and two traditional markets in New York City, long‐term rentals and hotels, to investigate whether Airbnb is a substitute to either one. Using data from InsideAirbnb, the American Community Survey (ACS), Zillow Research, and the City Planning Primary Land Use Tax Lot Output (PLUTO), we estimate three different models: (i) a fixed effect panel data model relating the number of listings to the number of hotels and socioeconomic variables; (ii) hedonic price regressions relating long‐term rents to the number of Airbnb host listings and prices; and (iii) a simultaneous equation model of supply and demand for long‐term rentals where rental supply and demand are functions of Airbnb nightly rates. We find that: (i) the numbers of host listings and guest reviews are higher in neighborhoods with higher concentration of hotels; (ii) there is a positive relationship between long‐term rents and both the number of Airbnb listings and Airbnb rates; (iii) the supply‐and‐demand simultaneous equations model shows a negative relation between the supply of properties for rent and Airbnb nightly rates; and (iv) the supply‐and‐demand simultaneous equations model shows a positive relationship between the demand for rentals and Airbnb nightly rates. These results are consistent with Airbnb being a substitute to both hotels and long‐term housing rentals.

Judging an Airbnb booking by its cover: how profile photos affect guest ratings

PurposeThis research aims to examine whether the facial appearances and expressions of Airbnb host photos influence guest star ratings.Design/methodology/approachThis research analyzed the profile photos of over 20,000 Airbnb hosts and the guest star ratings of over 30,000 Airbnb listings in New York City, using machine learning techniques.FindingsFirst, hosts who provided profile photos received higher guest ratings than those who did not provide photos. When facial features of profile photos were recognizable, guest ratings were higher than when they were not recognizable (e.g. faces too small, faces looking backward or faces blocked by some objects). Second, a happy facial expression, blond hair and brown hair positively affected guest ratings, whereas heads tilted back negatively affected guest ratings.Originality/valueThis research is the first, to the best of the authors’ knowledge, to analyze the facial appearances and expressions of profile photos using machine learning techniques and examine the influence of Airbnb host photos on guest star ratings.

Pricing Strategies of Porto’s Airbnb New Listings

Airbnb hosts’ pricing decisions are the choices hosts make when setting the daily rate for their listing of properties. Some Airbnb hosts have a long run approach, charging lower prices to attract more customers and achieve higher occupancy rates, while others have a short-run approach, charging higher prices to maximize the short-run opportunities from the market. The pricing strategy of Airbnb hosts is the key to their eventual success and plays an important role, since it influences their relationship with customers. Airbnb listings can be hard to price. Therefore, each Airbnb host faces an important decision when entering the market: What is the perfect daily rate to charge such that to achieve their goal? Major aspects, such as property location, type (private room, entire home, etc.) and amenities, target customers, other Airbnb competitors, thinking like a guest, the safety and beauty of the neighborhood, seasonality, etc., must be considered. Considering Airbnb’s exponential growth since it started in 2007, it is obvious that establishing a suitable pricing strategy is vital for any new host. The present paper uses information from the new listings in 2020 to investigate different hypotheses that explore the pricing strategies of Airbnb hosts for their new listings on the market. This study highlights, on one hand, the great need for Airbnb to encourage dynamic pricing among its new hosts and, on the other hand, the challenges faced by these hosts when they establish the price. An important characteristic of this article is the set of theoretical and methodological implications for the pricing strategy for the new Airbnb new hosts. Furthermore, this document reinforces the idea that the pricing strategy differs between cities and countries, emphasizing the strategy in the case of the new Airbnb new hosts.

Improving hosts’ pre-interaction capabilities for sustainability based on Airbnb host content emergence characteristics

The sharing of accommodation as a sustainable environmental solution for the lodging market is prevalent all over the world. However, the rapid expansion and low occupancy rate could be due to the accommodation hosts’ lack of attention to the pre-interaction content while reducing their carbon footprint, which have caused a significant impact on guests’ decision-making and prevented sharing accommodation. To improve the host pre-interaction capabilities and achieve the environmentally friendly potential of sharing accommodation, this research aims to explore the host expression characteristics including important topics and keywords of host pre-interaction content from a symbolic interaction perspective. Conducting the latent Dirichlet allocation machine learning model, keywords clustering characteristics emerged as main topics based on 38,814 listings from Airbnb in Beijing. The result of investigating the features in these topics and the word distribution in three types of properties shows that in a homogenous accommodation community, hosts who make the pre-interaction have more orders than those who do not. At the same time, the focus of hosts on expressing explicit and abundant topic symbols can effectively increase the attractiveness of their listings. However, accommodation hosts who just post a long text but do not emphasize listing key topics would not convince guests to use the accommodation. A variety of practical implications of findings has been discussed for sharing accommodation practitioners to answer the challenge of sustainability.

Exploring Airbnb Host Wellbeing and Host-Guest Conflicts in Network Hospitality.

Despite a plethora of studies examining hosting experiences of Airbnb guests, the wellbeing of hosts has received limited attention. Drawing on both top-down and bottom-up theories of wellbeing, we explore the different ways in which Airbnb enhances or diminishes host wellbeing using a multidimensional lens (material, relational and subjective wellbeing). Data is collected from in-depth interviews with twenty-two Airbnb hosts. We also identify tensions and conflicts in the host-guest relationship using the three interactional hospitality domains of commercial, social and private. Through a deductive process, we find that participating in Airbnb both enhances and diminishes the material, relational and subjective aspects of wellbeing for hosts. Inductively, we find that a lack of territorial boundaries in shared accommodation contribute to conflicts that reduce wellbeing. This exemplifies a tension that exists in the private-commercial domain of network hospitality provision. We provide implications for peer-to-peer accommodation providers on developing the managerial skills of hosts, and helping hosts set realistic expectations around hosting to reduce the conflicts and tensions that arise from the intersectionality of the various Airbnb hospitality domains in such a way that the wellbeing of hosts is enhanced.

Accommodating guests during pandemic times: a case-study of the Airbnb Host Community in Aarhus, Denmark

Purpose This paper explores how Airbnb hosts' experiences with and responses to the coronavirus disease 2019 (COVID-19) health crisis may differ according to their motivations to host and to the type and spatial layout of their Airbnb accommodation. Based on these insights, the paper reflects on the lessons that are learned for the future of short-term rentals. Design/methodology/approach This is a qualitative multi-method small-scale case study, which relies on in-depth interviews and a focus group discussion carried out with a group of hosts affiliated to the Airbnb Host Community in Aarhus, Denmark. Informed by an interpretivist approach, the study aims to make sense of people's subjective experiences with hosting on the Airbnb platform, and how they have continued and adapted their hospitality practices during the pandemic. Findings Participants' adaptive practices vary according to their motivations to host and the type of accommodation that they rent out. Although all hosts in this study now implement more intensive cleaning practices, hosts who stay with their guests onsite tend to take stricter preventative measures to avoid contamination and transmission of the virus in their social interactions with guests. On the contrary, hosts who rent out their entire properties and have minimal contact with their guests found themselves less affected by the pandemic's impacts and have had a continued demand for their properties. Social implications The COVID-19 pandemic has unevenly affected Airbnb hosts. Hosts who share their homes with guests require different adaptations to their daily behaviour and cleaning practices at home than hosts who do not stay with their guests and rent out entire properties. However, unlike professional hosts who largely or solely rely on Airbnb for their income, occasional home-sharing hosts tend to be more flexible in coping with cancelled or fewer bookings. Originality/value This study provides novel insights into the uneven impact of the COVID-19 pandemic on participants in the platform economies of tourism. It contributes to existing literature on the impacts of the pandemic on Airbnb's operations by showing how hosts' adaptive practices are informed by their subjective living conditions and the type of accommodation they can offer their guests.

From Homeowner to Airbnb Host: The Role of Trust and Perceived Value

ABSTRACT To investigate the effects of trust and perceived value on the intentions to engage in hosting Airbnb, this study builds a multivariate model to explore the difference exists between Airbnb hosts and potential hosts. The empirical results reveal that perceived value is a major motivation for homeowners, while trust becomes the primary driving force for hosts continuing to use Airbnb. Perceived usefulness, ease of use, risks of Airbnb, and familiarity and personal innovativeness of users are furtherly examined as secondary variables. This study provides practical implications for the accommodation sharing platforms to improve the e-service quality and formulate marketing strategies.

Political organizing and narrative framing in the sharing economyAirbnb host clubs in New York City

As cities accommodate, resist, and negotiate with the spread of so-called ‘sharing economy’ companies, the question of how these businesses actively construct new markets (or sub-markets) through political mobilization and rhetorical strategy has become increasingly salient. This paper explores the ways in which the home-sharing platform Airbnb has sought to carve out a regulatory and discursive space for operation through the political mobilization of its ‘hosts’ in New York City. Based on nearly two years of ethnographic research, the paper argues that host clubs are not merely top-down transmission belts for the company’s political lobbying strategy; beyond political organizing, they are also sites in which the very practices of hosting through Airbnb are affirmed, rehearsed, learned, and debated. On the one hand, Airbnb host clubs are both physical embodiments of, and mechanisms for, the narrative framing of ‘home-sharing’ as a particular kind of economic activity that is more democratic, inclusive, and sustainable than the traditional hospitality industry. On the other hand, Airbnb host clubs reveal and reflect the tensions – between hosts and Airbnb, and among hosts themselves – that persist over the practice of home-sharing. As the calls for tighter regulation and increased penalties for illegal short-term rentals continue to grow, however, the question of whether host clubs constitute a viable mechanism for political mobilization and regulatory reform remains an open one.

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

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

The Effect of Airbnb on Hotel Performance: Comparing Single- and Multi-Unit Host Listings in the United States

Extant research provides ample evidence that Airbnb has an adverse impact on hotel revenues and that a majority of Airbnb hosts offer multiple listings on the platform. Arguably, multi-unit host listings are the primary driving force for the associated decreases in hotel revenues. To test this proposition, this study examines the extent to which single- and multi-unit host Airbnb host listings have differing effects on hotel revenues. The results show that the adverse impact of Airbnb supply on hotel revenues was mainly driven by decreases in hotel prices rather than decreases in hotel demand. Contrary to expectations, single-unit host listings exerted greater downward pricing pressure on hotels than multi-unit host listings. These effects were consistently observed across hotel segments, with economy-scale hotels experiencing substitution effects in addition to pricing pressure. The findings have significant implications for researchers and stakeholders impacted by the sharing economy in the lodging industry.

Serving with a Smile on Airbnb: Analyzing the Economic Returns and Behavioral Underpinnings of the Host’s Smile

Non-informational cues, such as facial expressions, can significantly influence judgments and interpersonal impressions. Past research has explored how smiling affects business outcomes in offline or in-store contexts, yet relatively little is known about how smiling influences consumer choice in e-commerce settings. This paper explores the effect of smiling in the growing sharing economy context, specifically examining how a smile in an Airbnb host’s profile photo affects property demand. The study uses a facial attribute classifier to determine whether the host is smiling in their profile picture or not, and estimate the influence of a host smile in a longitudinal dataset of Airbnb bookings, controlling for a rich set of variables such as reviews, property characteristics, and the host’s age and gender. A smile in the host’s profile photo increases property demand by 1.9% on average. Further, gender moderates this effect, with smiling increasing demand for male hosts by 6.8%, compared to an insignificant increase for female hosts. An online experiment confirms this pattern, and explores the underlying mechanism. In particular, a moderated mediation analysis shows that smiling increases perceptions of the host’s warmth—to a greater extent for male than female hosts—which increases the likelihood of booking their property.