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Article
Publication date: 15 March 2023

Indranil Ghosh, Rabin K. Jana and Mohammad Zoynul Abedin

The prediction of Airbnb listing prices predominantly uses a set of amenity-driven features. Choosing an appropriate set of features from thousands of available amenity-driven…

Abstract

Purpose

The prediction of Airbnb listing prices predominantly uses a set of amenity-driven features. Choosing an appropriate set of features from thousands of available amenity-driven features makes the prediction task difficult. This paper aims to propose a scalable, robust framework to predict listing prices of Airbnb units without using amenity-driven features.

Design/methodology/approach

The authors propose an artificial intelligence (AI)-based framework to predict Airbnb listing prices. The authors consider 75 thousand Airbnb listings from the five US cities with more than 1.9 million observations. The proposed framework integrates (i) feature screening, (ii) stacking that combines gradient boosting, bagging, random forest, (iii) particle swarm optimization and (iv) explainable AI to accomplish the research objective.

Findings

The key findings have three aspects – prediction accuracy, homogeneity and identification of best and least predictable cities. The proposed framework yields predictions of supreme precision. The predictability of listing prices varies significantly across cities. The listing prices are the best predictable for Boston and the least predictable for Chicago.

Practical implications

The framework and findings of the research can be leveraged by the hosts to determine rental prices and augment the service offerings by emphasizing key features, respectively.

Originality/value

Although individual components are known, the way they have been integrated into the proposed framework to derive a high-quality forecast of Airbnb listing prices is unique. It is scalable. The Airbnb listing price modeling literature rarely witnesses such a framework.

Details

International Journal of Contemporary Hospitality Management, vol. 35 no. 10
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 23 October 2023

Mingming Hu, Lijing Lin, Minkun Liu and Shuai Ma

This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing…

Abstract

Purpose

This study aims to explore image-based visual price determinants (image features and visual aesthetic perception) and how image features affect Airbnb listing price on a sharing accommodation platform.

Design/methodology/approach

The study uses an SOR model and a hedonic price model to examine the connections between the characteristics of image features, visual aesthetic perception and Airbnb listing prices. The model is then examined by an econometric model using data from Insideairbnb.com.

Findings

Empirical results revealed that image features have a significant positive effect on visual aesthetic perception, visual aesthetic perception has a significant positive effect on Airbnb listing price and visual aesthetic perception has a significant mediating effect between image features and Airbnb listing price.

Originality/value

This study contributes to the relationship and effect mechanism among image features, visual aesthetic perception and Airbnb listing price and has some implications for both property operators and the sharing accommodation platform.

目的

本研究探讨了基于图像的视觉价格决定因素(图像特征和视觉美学感知)以及图像特征如何影响共享住宿平台Airbnb价格。

设计/方法/途径

本研究采用SOR模型和hedonic价格模型来检验图像特征特征、视觉美感与Airbnb房源价格之间的关系。然后使用Insideairbnb.com上的数据, 通过计量经济学模型对该模型进行检验。

研究结果

实证结果显示:1)图像特征对视觉美学感知有显著的正向影响; 2)视觉美学感知对Airbnb价格有显著的正向影响; 3)视觉美学感知在图像特征和Airbnb价格之间有显著的中介效应。

独创性/价值

本研究有助于探讨图像特征、视觉美学感知和Airbnb价格之间的关系和影响机制, 对房源经营者和共享住宿平台都有一定的借鉴意义。

Objetivo

Este estudio explora los determinantes visuales del precio basados en las imágenes (características de las imágenes y percepción estética visual) y cómo afectan las características de las imágenes al precio de los anuncios de Airbnb en una plataforma de alojamiento compartido.

Diseño/metodología/enfoque

El estudio emplea un modelo SOR y un modelo de precios hedónicos para examinar las conexiones entre las características de los rasgos de la imagen, la percepción estética visual y los precios de Airbnb. A continuación, se examina el modelo mediante un modelo econométrico utilizando datos de Insideairbnb.com.

Resultados

Los resultados empíricos revelan que 1) las características de la imagen tienen un efecto positivo significativo sobre la percepción estética visual, 2) la percepción estética visual tiene un efecto positivo significativo sobre el precio de los anuncios de Airbnb, y 3) la percepción estética visual tiene un efecto mediador significativo entre las características de la imagen y el precio de los anuncios de Airbnb.

Originalidad/valor

Este estudio contribuye al mecanismo de relación y efecto entre las características de la imagen, la percepción estética visual y el precio del anuncio de Airbnb, y tiene algunas implicaciones tanto para los operadores inmobiliarios como para la plataforma de alojamiento compartido.

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: 26 January 2024

Ioulia Poulaki, Evi Chatzopoulou, Mary Constantoglou and Vaia Konstantinidou

This paper aims to examine how Airbnb has been transformed from an informal form of tourism accommodation into an emerging form of tourism e-micro-entrepreneurship through an…

Abstract

Purpose

This paper aims to examine how Airbnb has been transformed from an informal form of tourism accommodation into an emerging form of tourism e-micro-entrepreneurship through an interesting triangle consisting of three distinct parts: hosts, platform and guests.

Design/methodology/approach

Considering that the peer-to-peer response has sealed the sharing economy's success, research methodology involves primary research that focuses on the adeptness of Airbnb hosts as e-micro-entrepreneurs from the customers' perspective. A quantitative methodology was employed by applying a convenience sampling strategy through a structured questionnaire that was distributed online, resulting in a collection of 150 useable responses. A statistical analysis has been performed to test the research's objectives.

Findings

Driven by Airbnb hosts' entrepreneurial behavior in managing their listings and guests' responses, research findings led to the development of a post-conceptual IRMA model, which describes this particular form of hosting as an e-micro-entrepreneurship opportunity, while guests' satisfaction confirms the platform's performance and hosts' efforts in service quality provision.

Research limitations/implications

This study brings valuable insights to the tourism e-entrepreneurship literature through the assessment of the Airbnb platform and the hosts as e-micro-entrepreneurs, providing useful information to researchers and managers involved in the Sharing Economy's disruptive innovation and a more complete understanding of the drivers of Airbnb's consumer adoption.

Originality/value

Research on Airbnb mainly focuses on service quality from the customer perspective, while the existing literature does not highlight how a new type of e-micro-entrepreneurship has emerged by operating in the sharing economy's disruptive innovation ecosystem, which illustrates the factors that motivate hosts and guests to share accommodation services in an equilibrium bond.

Details

Journal of Hospitality and Tourism Insights, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9792

Keywords

Open Access
Article
Publication date: 11 July 2023

Maja Golf-Papez and Barbara Culiberg

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and…

2013

Abstract

Purpose

This paper aims to examine the types of user misbehaviours in the sharing economy (SE) context. SE offers a fruitful study setting due to the scope of potential misbehaviour and the expanded role of consumers.

Design/methodology/approach

The study drew on online archival data from the AirbnbHell.com website, where people share their stories about their Airbnb-related negative experiences. The authors reviewed 405 hosts’, guests’ and neighbours’ stories and coded the identified forms of misbehaviours into categories. The typology thus developed was validated in the context of the Uber Rides service.

Findings

User misbehaviours in the SE context can be distinguished based on the domain in which the user role is violated and the nature of violated norms. These two conceptual distinctions delineate a four-fold typology of user misbehaviours: illegal, unprofessional, unbefitting and uncivil behaviours.

Research limitations/implications

The trustworthiness of the stories could not be assessed.

Practical implications

The presented typology can be used as a mapping tool that facilitates detection of the full scope of misbehaviours and as a managerial tool that provides ideas for effective management of misbehaviours that correspond to each category.

Originality/value

The paper presents the first empirically derived comprehensive typology of user misbehaviours in SE settings. This typology enables classification of a broad set of misbehaviours, including previously overlooked unprofessional behaviours carried out by peer-service providers. The study also puts forward a revised definition of consumer misbehaviours that encompasses the impact of misbehaviours on parties not directly involved in the SE-mediated exchange.

Details

European Journal of Marketing, vol. 57 no. 13
Type: Research Article
ISSN: 0309-0566

Keywords

Article
Publication date: 26 April 2023

Jian-Wu Bi, Ying Wang, Tian-Yu Han and Kun Zhang

The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of…

Abstract

Purpose

The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of homestays and additionally considers the accommodation’s attribute performance and level of sharing.

Design/methodology/approach

To achieve the research aims, more than 9,738,335 items of user-generated content concerning 743,953 Airbnb listings covering 35 cities were collected as the study data. These data are analyzed through hierarchical regression.

Findings

The results show that all three dimensions of home feeling positively affect the online rating; all three dimensions negatively moderate the relationship between attribute performance and online rating; the size of the moderating effect of each dimension on the relationship between attribute performance and online rating gradually increases in the order home-as-practical, home-as-social and home-as-attachment; and as the level of sharing increases, the moderating effect of home feeling on the relationship between attribute performance and online rating diminishes.

Research limitations/implications

This study contributes to the literatures on the role of home feeling in homestays, the online rating of homestays and the motivations of guests who choose different room types. The findings of this study can help hosts better understand the formation of online rating of homestays, make targeted improvements in rooms and services and create a home feeling for specific degrees of sharing. This in turn will help them to improve the online rating of their homestays, establish an excellent online reputation and, ultimately, increase sales.

Originality/value

This study advances knowledge by confirming three dimensions of home feeling not only have direct positive impacts on online rating but also mitigate the impact of attribute performance on online rating. This effect differs significantly in magnitude with the degree of sharing.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 13 October 2022

Garima Negi and Smita Tripathi

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research…

1122

Abstract

Purpose

The paper intends to review academic research on peer to peer (P2P) accommodation sharing, notably Airbnb, for 2010–2022 and to identify the knowledge gaps for future research directions.

Design/methodology/approach

Numerous databases were searched using keywords. Based on the central theme of the research papers, the papers were divided into eight segments—consumer behavior, host behavior, host–guest relationship (HGR), trust in Airbnb, dominant theories in Airbnb, Airbnb regulation, Airbnb and hotels and macro impacts of Airbnb. In-depth content analysis resulted in the final 101 papers for inclusion.

Findings

The review advances comprehension of the Airbnb phenomenon by enriching the literature with new and most recent studies. Most existing Airbnb research has been conducted in Europe, USA/Canada, followed by Asian countries like China, Singapore, S. Korea and India. Future studies should include South America, Africa and other developing nations. More cross-cultural studies are required to understand consumer and host behavior in different cultural settings. Numerous proposals to fulfill the research gaps identified by the paper are discussed.

Practical implications

The study will give better insights into the spiraling P2P accommodation economy. The study will be useful to researchers, scholars, Airbnb, the hotel industry, vacation rental players and destination marketing organizations by relating the study findings to practical competition analysis. The study provides deeper insights into the decision-making process of both guests and hosts by examining the relevant motivators and constraints. It will also assist the Airbnb platform in identifying its strength over the traditional hotel industry and other vacation rentals. The findings will also assist policymakers in better controlling the Airbnb phenomena by providing a comprehensive view of the micro and macro environment.

Originality/value

The paper includes the most recent studies from Asian countries like India, Singapore, China, Korea and Taiwan, not covered by earlier reviews. Prior studies mainly focused on European and American countries. Also, the paper tried to cover the macro impacts of Airbnb in-depth and the effects of COVID-19.

Details

Journal of Hospitality and Tourism Insights, vol. 6 no. 5
Type: Research Article
ISSN: 2514-9792

Keywords

Article
Publication date: 8 February 2024

Veronica Leoni, Pierpaolo Pattitoni and Laura Vici

We challenge the conventional approach to distinguish between professional and non-professional Airbnb hosts by solely using the number of managed listings.

Abstract

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.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

Keywords

Open Access
Article
Publication date: 7 December 2023

Mohamed Ahmed Qotb Sakr, Mohamed H. Elsharnouby and Gamal Sayed AbdelAziz

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3…

Abstract

Purpose

This paper aims to address three research questions (1) Who is the main stakeholder that shapes Airbnb experience, (2) Does Airbnb offers an authentic travel experience? and (3) What should be the future research trends in Airbnb?

Design/methodology/approach

This paper uses the systematic literature review (SLR) with a well-defined protocol, research strategy and methods to answer the research questions.

Findings

The review revealed that while Airbnb plays a significant role as the platform provider, the stakeholders influencing the experiences are multifaceted. Hosts, guests, local communities and even regulatory bodies all contribute to shaping the overall Airbnb Experience ecosystem. Hosts, in particular, have a crucial role in curating and delivering unique experiences, which significantly impacts the quality and authenticity of the offerings. On the question of whether Airbnb offers an authentic travel experience, the review uncovered mixed findings. For examples, some studies emphasized the potential for Airbnb to provide authentic and local experiences, allowing travelers to engage with the community and cultural aspects of a destination. However, other studies raised concerns about the commodification and standardization of experiences, leading to a potential loss of authenticity.

Originality/value

This paper is different from previous SLR where previous research systematically reviewed; motivations to use and choose Airbnb, institutionalization of Airbnb, stakeholders of Airbnb. This paper addresses authentic experience as a factor that influences activity participation.

Details

Journal of Humanities and Applied Social Sciences, vol. 6 no. 1
Type: Research Article
ISSN: 2632-279X

Keywords

Article
Publication date: 8 December 2022

Andrea Calabro, Tahir M. Nisar, Mariateresa Torchia and Hsiao-Ting Tseng

In this study, the authors examine how organizational-, systems- and interpersonal-level trust may be required for a smooth functioning of the firms in the sharing economy (SE)…

Abstract

Purpose

In this study, the authors examine how organizational-, systems- and interpersonal-level trust may be required for a smooth functioning of the firms in the sharing economy (SE). The research objective is to explore the trust-building mechanisms of Airbnb, a leading SE organization, and its aim to foster generalized trust. An investigation of the Airbnb's promotion of different trust-building mechanisms will allow to evaluate their effectiveness in how they can help overcome scepticism and distrust between the transacting parties. Consequently, the authors can develop a unique theoretical perspective on generalized trust in SE environments and better understand any trust-related barriers preventing SE transactions.

Design/methodology/approach

The authors employ a case study approach to investigate the research questions with the aim to fully understand the abstract and complex nature of trust. They focus on Airbnb as the company enjoys a leading market position, being a sharing economy firm. Moreover, the personal nature of accommodation sharing, which is the business of Airbnb, increases users' trust requirements, and so the company must take active steps to promote trust between the transacting parties. The authors adopt thematic analysis to execute the data analysis of the study's findings, which are derived from emergent themes and directed by the research objectives and relevant literature.

Findings

The results show that users of Airbnb are concerned about the danger of opportunistic hosts, although they are primarily motivated to use the company's services due to its economic benefits. Nevertheless, the success of Airbnb platform stems from the trust that the company has succeeded in establishing among its users, in particular interpersonal trust. Analysis reveals that generalized trust is fostered at an interpersonal level in the form of peer reviews, at an organizational level in terms of brand familiarity and at a systems level in regards to interface design.

Originality/value

The authors advance the argument that confidence to transact in the social economy stems from a combination of three levels of trust, including organizational-, systems- and interpersonal-level trust. These findings contribute to the body of trust research in information technology and people literature from its unique investigative setting, whilst simultaneously strengthening the primarily speculative research on SE with in-depth empirical evidence.

Details

Information Technology & People, vol. 36 no. 7
Type: Research Article
ISSN: 0959-3845

Keywords

1 – 10 of 69