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A big data approach to map the service quality of short-stay accommodation sharing

Meisam Ranjbari (Department of Economics and Statistics, University of Turin, Torino, Italy)
Zahra Shams Esfandabadi (Department of Environment, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, Torino, Italy)
Simone Domenico Scagnelli (School of Business and Law, Edith Cowan University, Joondalup, Australia)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 29 June 2020

Issue publication date: 4 August 2020

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Abstract

Purpose

The purpose of this paper is to map the service quality (SQ) of Airbnb, to provide additional insight for such top player of short-stay accommodation in the sharing economy context.

Design/methodology/approach

A mixed-method approach is used in two phases. In the qualitative phase, 112,138 online review comments of Airbnb guests were analyzed to generate the service attributes. In the quantitative phase, an online survey (n = 814) was conducted to calculate the performance and importance values of extracted attributes to plot them in an Importance-Performance Analysis (IPA) matrix.

Findings

A holistic image of the Airbnb extracted service attributes was presented through the IPA plot. Four types of SQ strategies were proposed, considering the actions priority. “Price reasonability” was the most important service attribute of Airbnb for guests, whereas “Check-in flexibility” was the best performed one.

Practical implications

The results shed light on the most relevant SQ attributes of Airbnb and proposed suitable strategies that can prioritize relevant stakeholders’ actions and decisions. The study significantly contributes to all decision makers involved in the short-stay accommodation sharing industry to further understand and develop SQ.

Originality/value

This research, using a comprehensive hybrid method, opens a lens to see more clearly the positioning of different attributes of Airbnb service from importance and performance viewpoints. As a contribution, the SQ of Airbnb was mapped by conducting an IPA for the first time in the literature.

Keywords

Citation

Ranjbari, M., Shams Esfandabadi, Z. and Scagnelli, S.D. (2020), "A big data approach to map the service quality of short-stay accommodation sharing", International Journal of Contemporary Hospitality Management, Vol. 32 No. 8, pp. 2575-2592. https://doi.org/10.1108/IJCHM-02-2020-0097

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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