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Article
Publication date: 23 March 2020

Billie Ann Brotman

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Social implications

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.

Originality/value

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.

Details

Journal of Property Investment & Finance, vol. 38 no. 2
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 12 February 2019

Heejeong Han, Seunghun Shin, Namho Chung and Chulmo Koo

This paper aims to explain a guest’s purchase decision in Airbnb from the perspective of Aristotle’s appeals. In host-created information, the authors investigate which…

3194

Abstract

Purpose

This paper aims to explain a guest’s purchase decision in Airbnb from the perspective of Aristotle’s appeals. In host-created information, the authors investigate which information appeals are significantly considered by guests.

Design/methodology/approach

It is hypothesized that a guest’s purchase would be affected by the host-created information’s ethos, pathos and logos.

Findings

For the ethos, the super host badge and host review have positive impacts on the purchase; for the pathos, the positive impact of the use of social words is significant. For the logos, the authors have determined that although the price, place picture and star-rating have positive impacts on the likelihood of a purchase, the occupancy has a negative impact on it.

Research limitations/implications

The dependent variable, the number of place reviews, cannot represent the exact number of purchases. Other possible influential factors, such as direct communications between hosts and guests, are not examined.

Practical implications

The findings suggest guidelines for Airbnb and its host users. Specifically, the management of normal host users is revealed as a necessary process for Airbnb’s development. For host users, several guidelines on how to attract more guests effectively are provided.

Originality/value

In contrast to other studies on Airbnb, various pieces of information are considered from holistic perspectives, and each piece’s impact on the sharing behavior is understood by means of a unique theoretical model that is based on Aristotle’s appeals.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 20 November 2017

Moloud Abdar and Neil Y. Yen

This research intends to look at the regional characteristics through an analysis of crowd preference and confidence, and investigates how regional characteristics are going to…

Abstract

Purpose

This research intends to look at the regional characteristics through an analysis of crowd preference and confidence, and investigates how regional characteristics are going to affect human beings at all aspects in a scenario of sharing economy. The purpose of this paper is to introduce an approach to provide an understandable rating score. Furthermore, the paper aims to find the relationships between different features classified in this study by using machine learning methods. Furthermore, due to the importance of performance of methods, the performance of the features is also improved.

Design/methodology/approach

The Rating Matching Rate (RMRate) approach is proposed to provide score in terms of simplicity and understandability for all features. The relationships between features can be extracted from accommodation data set using decision tree (DT) algorithms (J48, HoeffdingTree, and REPTree). Usability of these methods was evaluated using different metrics. Two techniques, “ClassBalancer” and “SpreadSubsample,” are applied to improve the performance of algorithms.

Findings

Experimental outcomes using the RMRate approach show that the scores are very easy to understand. Three property types are very popular almost in all of selected countries in this study (“apartment”, “house”, and “bed and breakfast”). The findings also indicate that “Entire home/apt” is the most common room-type and 4.5 and 5 star-rating are the most given star-rating by users. The proposed DT algorithms can find the relationships between features significantly. In addition, applied CB and SS techniques could improve the performance of algorithms efficiently.

Originality/value

This study gives precise details about the guests’ preferences and hosts’ preferences. The proposed techniques can effectively improve the performance in predicting the behavior of users in sharing economy. The findings can also help group decision making in P2P platforms efficiently.

Details

Library Hi Tech, vol. 35 no. 4
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 15 May 2023

Catherine Prentice and Adam Pawlicz

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the…

Abstract

Purpose

This paper aims to examine the primary supply data sources that have been used for research into the sharing economy, and the advantages and limitations of these sources in the literature.

Design/methodology/approach

To address the research aims, this study conducted a systematic literature review and content analysis of all relevant articles. Following the review, the methodological sections of the selected papers were examined to identify the characteristics and limitations of all data sources used in the papers.

Findings

This study revealed several limitations of the use of three major data sources, namely, web scraping with self-made bots, inside Airbnb and AirDNA, for sharing economy research. The review shows that the majority of the selected papers did not acknowledge any limitations, nor did they discuss the quality of the data sources.

Research limitations/implications

The findings of this paper can serve as guidelines for selecting appropriate data sources for research into the sharing economy and cautions researchers to address the limitations of the data sources used.

Originality/value

To the best of the authors’ knowledge, this is the first study that explores the advantages and limitations of data sources used in short-term rental market research.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 5 September 2020

Edward Koh

This paper aims to examine the issues faced by cities known for their struggles with over-tourism, before and during the Covid-19 pandemic. Opportunities to overcome over-tourism…

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Abstract

Purpose

This paper aims to examine the issues faced by cities known for their struggles with over-tourism, before and during the Covid-19 pandemic. Opportunities to overcome over-tourism in a post-Covid-19 world are discussed.

Design/methodology/approach

This paper is a review of the fundamental issues of over-tourism before and during the Covid-19 pandemic.

Findings

The pandemic has turned the state of tourism in many cities from “over-tourism” to “no tourism”, prompting massive state intervention from governments, regardless of their political ideology. The pandemic has also been more effective than top-down governmental orders and ground-up green initiatives to reduce pollution within a short span of time.

Practical implications

Many have been left behind by the competitive nature of globalisation, and the Covid-19 pandemic could present a case for governments to play a larger role in improving their citizens’ quality of live. These would include a fundamental shift in focus to jobs (instead of gross domestic products) by governments, increased investment in public works and environment-friendly infrastructure and expanding public regulatory and enforcement roles in areas such as crowd control and inspection of home rentals for regulatory compliance.

Social implications

When normalcy returns and tourists begin to flock to destinations and attractions, there should be a much higher awareness amongst both tourists and locals of the maintenance of personal hygiene and of the need for safe distancing while in dense crowds. A new social norm should emerge.

Originality/value

A heightened sense of material, community, emotional and health and safety well-beings of local residents would ease concerns and perceptions of over-tourism.

Details

International Journal of Tourism Cities, vol. 6 no. 4
Type: Research Article
ISSN: 2056-5607

Keywords

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