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Standing out from the crowd – An investigation of the signal attributes of Airbnb listings
Bin Yao1; Richard T.R. Qiu2; Daisy X.F. Fan3; Anyu Liu4; Dimitrios Buhalis3
2019
Source PublicationInternational Journal of Contemporary Hospitality Management
ISSN0959-6119
Volume32
Abstract

Purpose

Due to product diversity, traditional quality signals in the hotel industry such as star ratings and brand affiliation do not work well in the accommodation booking process on the sharing economy platform. From a suppliers’ perspective, this study aims to apply the signaling theory to the booking of Airbnb listings and explore the influence of quality signals on the odds of an Airbnb listing being booked.

Design/methodology/approach

A binomial logistic model is used to describe the influences of different attributes on the market demand. Because of the large sample size, sequential Bayesian updating method is utilized in hospitality and tourism field for the first attempt.

Findings

Results show that, in addition to host-specific information such as “Superhost” and identity verification, attributes including price, extra charges, region competitiveness and house rules are all effective signals in Airbnb. The signaling impact is more effective for the listings without any review comments.

Originality/value

This study contributes to the literature by incorporating the signaling theory in the analysis of booking probability of Airbnb accommodation. The research findings are valuable to hosts in improving their booking rates and revenue. In addition, government and industrial management organizations can have more efficient strategy and policy planning.

KeywordSignaling Theory Big Data Airbnb Binomial Logistic Model Booking Probability Sequential Bayesian Updating Sharing Economy
DOIhttps://doi.org/10.1108/IJCHM-02-2019-0106
Language英语
Fulltext Access
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Document TypeJournal article
CollectionFaculty of Business Administration
DEPARTMENT OF INTEGRATED RESORT AND TOURISM MANAGEMENT
Affiliation1.School of Economics, Liaoning University, Shenyang, China
2.Department of Integrated Resort and Tourism Management, Faculty of Business Administration, University of Macau, Taipa, Macao
3.eTourism Lab, International Centre for Tourism and Hospitality Research, Bournemouth University, Poole, UK
4.School of Hospitality and Tourism Management, University of Surrey,Guildford, UK
Recommended Citation
GB/T 7714
Bin Yao,Richard T.R. Qiu,Daisy X.F. Fan,et al. Standing out from the crowd – An investigation of the signal attributes of Airbnb listings[J]. International Journal of Contemporary Hospitality Management,2019,32.
APA Bin Yao,Richard T.R. Qiu,Daisy X.F. Fan,Anyu Liu,&Dimitrios Buhalis.(2019).Standing out from the crowd – An investigation of the signal attributes of Airbnb listings.International Journal of Contemporary Hospitality Management,32.
MLA Bin Yao,et al."Standing out from the crowd – An investigation of the signal attributes of Airbnb listings".International Journal of Contemporary Hospitality Management 32(2019).
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