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San Francisco started regulating short-term vacation rentals on rooms/apartments/houses located within city limits in September 2019. The objectives of this conceptual-scenario and regression study are to calculate the present value of the net earnings for a short-term residential rental property located in San Francisco pre-regulation and post-regulation, and consider a financial reason motivating households to list properties as short-term rentals.

A present value approach is used to estimate the value of rental space to tourists prior to the passage of San Francisco's short-term rental regulations compared to post-rental rules. Table 2 shows pre- and post-income scenarios. Price increases of +20, +40 and +60 percent over the initial base rate failed to restore host earnings to pre-registration levels. The present value model calculates the net revenue less net cost associated with listing a property. The regression model uses the number of listings as the dependent variable, and housing prices divided by weekly wages as independent variables.

The short-term rental regulations significantly reduce the profitability associated with short-term tourist stays offered by hosts and listed by online platforms. A host earns pre-regulation income when average daily rents increase by approximately 71.5 percent. It will likely limit income earned by hosts and Airbnb and other shared housing website platforms due to the reduced number of rental days allowed for shared housing caused by ordinances and host enrollment restrictions. The regression model results suggest that homeowners were listing properties for rent to help cover higher priced property purchases.

Airbnb, VRBO, Booking.com, and HomeAway are all private companies; this means that financial information is not publicly available. HomeAway, VRBO, and Booking.com are companies owned by Expedia. FlipKey is owned by TripAdvisor. Due to limited public information regarding income statements and property listing trends, regression analysis and descriptive statistics cannot be generated using audited financial statements.

Rent control restriction frequently sets the maximum price below the market-clearing price, which results in limited supply but increase in demand for housing. The San Francisco regulations outlaw second-home rentals and seriously limit the availability of other rentals to tourists. FlipKey and HomeAway tend to rent second homes, which San Francisco now bars from being rented for short-term.

The San Francisco restrictions were enacted with the goal of increasing the supply of rental housing available to permanent residents by restricting short-term rentals. This may have limited short-term benefits to permanent residents, but in the long term lowers income associated with single-family housing which will encourage housing arrangements that would avoid leasing restrictions and lower the number of new houses built. Other cities also have a history of rent controls, and are experiencing housing shortages and at the same time attracting large numbers of tourists. These cities may be motivated to enact similar rental restrictions as those approved in San Francisco.

These short-term rental restrictions just started being implemented and enforced. A court decision upheld them. There were media reports outlining the restrictions, but enforcement has just started, so no research papers have been written about San Francisco. Prior research studies have not used net present value analysis to calculate the loss to the host by enacted ordinances restricting tourists’ length of stay and have neither tried to explain why homeowners are listing properties for short-term rentals.

This study aims to examine the permit changes enacted by the city of Portland, Oregon, USA, on the construction and subsequent short-term rental of tiny homes. The permitting process was eased by the city in 2014. The city’s enforcement of occupancy and rental ordinances, sometimes called Airbnb laws, were tightened in 2019. The new code restrictions are tighter than the rental codes that existed previously.

This paper uses time-series data to first consider the thesis that relaxing building permit requirements for tiny homes has encouraged legal construction and increased the number of applications filed with the city planning office. The number of permits was the dependent variable and time-sensitive dummy variable was the independent variable. An adjusted T-statistic was calculated using a least-squares regression model with a moving average autocorrelation adjustment. The second regression model considers the financial relationship between active listings on Airbnb and HomeAway to a housing price coverage ratio and the aggregated dynamic-factor model used to calculate the economic activity index for Portland.

There were two reported case study findings. The first regression used a dummy variable measuring the application response to permit easing. It was positive and significant. The second finding measures active host listings on Airbnb whether they are directly associated with the calculated multiple of the changes in the S&P/Case–Shiller housing price index low tier divided by weekly employee income. Higher numbers for this coverage ratio suggest that listings on short-term rental platforms are increasing directly with the ratio. The economic activity index is insignificant when predicting the level of listings. Regression results indicate that property owners are financially motivated to list dwellings as visitor rentals and possibly motivated to install tiny homes behind their primary residences as short-term rental units. Local economic conditions do not seem to influence the number of properties listed on short-term rental websites.

Higher coverage ratios encourage property owners to list dwellings on short-term rental websites in the absence of enforceable rental restrictions. Without a method to quickly and feasible identify owners violating short-term rental restriction legislation and enforce fines there is a tendency for active listings to grow in a locale. San Francisco, California, under its new short-term rental ordinance requires online websites such as Airbnb to enforce permit requirements. San Francisco’s ordinance change seems to have resulted in a dramatic drop in active listings available for visitor rentals.

Information published by Inside Airbnb and Airdna does not separate entire dwelling information into categories such as single-family detached houses; tiny homes; apartments; or condominiums ownership types. Even public housing units are sometimes listed as short-term rentals. The aggregate data makes the relationship between active listings and the coverage ratio difficult to interpret. Listing information is limited and only available for a three-year rolling cycle on a quarterly basis for the city of Portland, Oregon.

Future research studies could consider how tiny homes might play a role in providing permanent housing to local residents or for providing a shelter for the homeless in cities experiencing acute long-term rental shortages. Does limiting the number of homes available as short-term visitor rentals noticeably increase the quantity of housing and lower the monthly rental rates available to permanent residents of the city? Cities have passed short-term rental codes with the objective of increasing the availability of rental housing available to residents at affordable prices.

Prior research studies focused on who purchases tiny homes; tiny homes used as housing for the homeless; communities composed of tiny homes; and the connection between tiny home living and political activism. The study herein links permit changes to tiny-home building applications. It uses the home price index low tier and the economic condition index for the Portland metropolitan area to predict the number of active listings on Airbnb and HomeAway websites pre-regulation enforcement.

This study aims to investigate how the COVID-19 pandemic has impacted and changed Airbnb market in the Greater Melbourne area in terms of its temporal and spatial patterns and identify possible shifts in underlying trends in travel activities.

A panel data set of Airbnb listings in Melbourne is analysed to compare temporal patterns, spatial distribution and lengths of stay of Airbnb users before and after the COVID outbreak.

This study found that the COVID disruption did not fundamentally change the temporal cycle of the Airbnb market. Month-to-month fluctuations peaked at different levels from pre-pandemic times mainly because of lockdowns and other restrictive measures. The impact of COVID-19 disruptions on neighbourhood-level Airbnb revenues is associated with distance to CBD rather than number of COVID cases. Inner city suburbs suffered major loss during the pandemic, whereas outer suburbs gained popularity due to increased domestic travel and long stays. Long stays (28 days or more, as defined by Airbnb) were the fastest growing segment during the pandemic, which indicates the Airbnb market was adapting to increasing demand for purposes like remote working or lifestyle change. After easing of COVID-related restrictions, demand for short-term accommodation quickly recovered, but supply has not shown signs of strong recovery. Spatial distribution of post-pandemic supply recovery shows a similar spatial variation. Neighbourhoods in the inner city have not shown signs of significant recovery, whereas those in the middle and outer rings are either slowly recovering or approaching their pre-COVID levels.

The COVID-19 pandemic has significantly impacted short-term rental markets and in particular the Airbnb sector during the phase of its rapid development. This paper helps inform in- and post-pandemic housing policy, market opportunity and investment decision.

To the best of the authors’ knowledge, this is one of the first attempts to empirically examine both temporal and spatial patterns of the COVID-19 impact on Airbnb market in one of the most severely impacted major cities. It is one of the first attempts to identify shifts in underlying trends in travel based on Airbnb data.

This viewpoint paper aims to provide reflections on the role of second homes in the tourism and housing markets together with future lines of research during and after the first outbreak of the COVID-19 (coronavirus disease 2019) pandemic. The authors aim to review the epistemological evolution of the term “second homes” because of the pandemic, as well as to unfold possible short-, medium- and long-term effects that could place second homes at the center of tourist activity and of the tourist rental market profitability.

This paper is based on published research studies about the definition of the term “second homes”, as well as media sources related to their role during the current situation of the first outbreak of the COVID-19 pandemic.

In the early stages of the pandemic, second-home owners migrated from crowded cities to low-density areas, being vectors of transmission of the virus. Now, a potential shift in tourist preferences could position second homes at the center of tourist activity as soon as travel restrictions are reduced. This could intensify existing processes of commodification of housing, empowering accommodation platforms and situating the potential for profiteering around the tourist rental market. Parallely, international interests in migrating from crowded cities to low-density areas could also be triggered.

This viewpoint is presented as the confinement measures associated with the new pandemic are being de-escalated in most of the western countries. It is expected that sharing it will provide insights to researchers and practitioners to better plan their research around secondary housing. Its role should be analysed from different perspectives: in the spread of the virus to low-density areas to anticipate mitigation actions in future outbreaks; in the recovery process of (domestic) tourism; in the processes of commodification and financialization of housing in tourist areas; and their impacts on local residents.

This paper aims to explore the effects of a surge in tourism short-term rentals (STR) on housing prices in municipalities within Portugal’s two largest Metropolitan Statistical Areas.

This study applies the difference-in-differences (DiD) methodology by using a feasible generalized least squares (FGLS) estimator in a seemingly unrelated regression (SUR) equation model.

The results show that the liberalization of STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. This transfer led to a leftward shift in the housing supply and a consequent increase in housing prices. These price increases are much higher than those found in previous studies on the same subject. The authors also found that municipalities with more STR had low housing elasticities, which indicates that adjustments to the transfer of real estate from housing to tourism were made by increasing house prices, and not by increasing supply quantities.

The study suggests that an unforeseen consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases due to inelastic housing supply.

This is the first time that the DiD methodology has been applied in real estate markets using FGLS in a SUR equation model and the authors show that it produces more precise estimates than the baseline OLS FE. The authors also find evidence of a supply shock provoked by STR.

The purpose of this paper is to explore regulatory issues of short-term rentals (STR) and evaluate what constitutes effective regulation of STR by analyzing the STR ordinance in the City of Charleston, South Carolina, as well as reviewing the regulation process the City took.

In this case study, the study employed a documentary research method (Ahmed, 2010) using multiple sources, including government documents, historical statistics and local publications. Prior to analyzing documents, face-to-face interviews with a couple of key government officials were conducted to understand the overall context of the regulation processes as well as to obtain primary information and data pertaining to Charleston’s STR regulation processes.

The study identified three noteworthy points. First, the legalization process was transparent and democratic; opportunities for stakeholder participation in crafting the Charleston’s ordinance included the establishment of the STR Task Force and public listening sessions. Second, the Charleston’s STR regulation is designed to protect non-participating residents and the historic characters of its neighborhoods; several measures (e.g. strict eligibility, operational restrictions, licensing and permitting, enforcement) protect non-participants and the neighborhood overall, while the City allows STR to be legal. Third, there is a unique enforcement mechanism and tourism-related governance structure; dedicated staff in the Department of Livability and Tourism enforce the STR laws in Charleston.

Empirical analysis of the STR regulations has never been established. The study provides useful and timely insights for local governments, destination management organizations, tourism scholars, and stakeholders in tourism cities to advance the discussions and debates around STR regulations.

This study aims to explore the impacts of Airbnb listings on land values in the Austin, Texas, USA area, particularly on single-family homes. The goal of the analysis is to shed light on how greatly and in what direction Airbnb is affecting the housing market, with an emphasis on the spatial distribution of its effects.

The analysis in this paper is performed using three distinct models on a data set of land parcel data within Travis County: an ordinary least squares regression model, a geographically weighted regression (GWR) aimed at detecting the influence of variables at the census tract level, and a Bayesian approach, which describes spatial and temporal effects on the data.

The findings of the analysis indicate that across the years 2013 to 2019, higher numbers of Airbnb listings were associated with lower percentage increases in land value in certain tracts in the northern and eastern parts of the city. Additionally, the results of the Bayesian model indicated that much of the change in land value can be attributed to unobserved factors within census tracts.

The contribution of this study to the existing literature is its analysis of the spatial and temporal analysis of the effects of Airbnb listings on land value using a GWR and a Bayesian model. Also, as the negative correlation found in the study departs from previous research, this paper may provide policymakers insight into the complex spatial distribution and conflicting effects of Airbnb listings across distinct parts of cities.

The “sharing economy” has blurred the lines between personal and commercial operations for many sectors of the economy. A convergence has occurred between hotel companies and home sharing platforms, as Airbnb is investing in brick-and-mortar hotels, and conversely hotel companies are investing in home sharing platforms as each of the sectors tends to mimic the other. Important aspects for the hosts of Airbnb are the quality of social interaction between guest and host and the level of authenticity of social exchanges provided by interactions with locals. There is both a quantitative and qualitative demonstration of professionalization within Airbnb's organization. The aim of this research is twofold: to measure to what extent guests are aware of the professional level of the host and to evaluate the importance of these professional aspects at the different moment of the vacation process (booking, stay, and post experience).

The expansion of online platforms for renting tourist accommodations has given rise to a great deal of controversy in society. Likewise, the arrival of tourists in residential settings has led to a wide range of positive and negative impacts, resulting in conflicts between different stakeholders. The purpose of this paper is to analyze whether there is variation in the perception of the impacts associated with peer-to-peer accommodation platforms among different stakeholders? Additionally, it also seeks to investigate what kind of impacts generate the highest level of conflict among stakeholders?

Given the relative novelty of the problem, this paper proposes an exploratory study that sheds light on some of the main issues with the purpose of supporting further research in the future. The aim is to analyze which impacts are perceived as more positive or negative by each group and to create indexes of conflict for these groups regarding their perception of the impacts. This study is based on fieldwork carried out in April 2020, which consists of 600 online surveys of local residents in the city of Granada. This city, one of Spain’s main tourist spots, suffers the highest tourist pressure in the country.

The exploratory study suggests that the greatest consensus is generated in the assessment of economic impacts, either negative or positive. The greatest conflicts are related to the assessment of the effect of this activity on housing preservation. The group comprising accommodation owners of tourist flats is the one that shows a more dissenting opinion from the rest, confronting especially the group formed by citizens whose income depends on tourism.

There is a lack of studies on the perception of tourism impacts associated with online tourism rental platforms. This is the first study to analyze both, how the main stakeholders associated with this activity assess the different impacts derived from this form of tourist accommodation as a whole and the conflicts derived from such an assessment. An additional innovation is that the analysis investigates the potential fear of disease transmission caused by tourists. It would be interesting to continue this research by applying the same questionnaire in different environments, such as rural areas or societies with different structures from the one analyzed here. Likewise, future in-depth analysis of some of the conflicts is recommended so as to ascertain their origin.

With the expansion in the tourism-related activities, the issue of overtourism has gained impetus rapidly in media and academic discourses. Many scholars believe that the concept is not novel and is rather associated with the familiar concept of carrying capacity of a tourist destination. The carrying capacity concerns have been raised earlier in recreational studies. These studies have focused on determining the maximum number of tourists that could be accommodated without any deterioration in the social, environmental and physical environment, and unacceptable decline in the tourist experience. However, as the tourism development projects expanded to attract more tourists, the host community reacted to the excessive tourism activities which hamper their lives. Consequently, overtourism or excessive tourism led to conflicts between the local community and tourists. The concerns aggravated as locals raised their voices against the unmanageable growth of tourism and irresponsible behaviour of tourists. This chapter presents a descriptive analysis of various conflicts that have taken place at tourist destination reported of overtourism. The authors have attempted to categorise the conflicts based on the capacity thresholds and suggested several management strategies that could be undertaken by respective destinations to resolve the conflicts. The major conflict categories are socio-cultural, socio-demographic, infrastructural, eco-spatial and economic. The authors expect that identification and categorisation of conflicts with related solutions would lead to better management of destinations. Furthermore, the destinations would adopt preventive measures to nip a potential conflict in the bud.