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Dynamics in accommodation feature preferences: exploring the use of time series analysis of online reviews for decomposing temporal effects

Thorsten Teichert (Chair of Marketing and Innovation, University of Hamburg, Hamburg, Germany)
Christian González-Martel (Department of Quantitative Methods in Economy, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain)
Juan M. Hernández (Department of Quantitative Methods in Economy, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain)
Nadja Schweiggart (Chair of Marketing and Innovation, University of Hamburg, Hamburg, Germany)

International Journal of Contemporary Hospitality Management

ISSN: 0959-6119

Article publication date: 20 November 2023

Issue publication date: 24 May 2024

282

Abstract

Purpose

This study aims to explore the use of time series analyses to examine changes in travelers’ preferences in accommodation features by disentangling seasonal, trend and the COVID-19 pandemic’s once-off disruptive effects.

Design/methodology/approach

Longitudinal data are retrieved by online traveler reviews (n = 519,200) from the Canary Islands, Spain, over a period of seven years (2015 to 2022). A time series analysis decomposes the seasonal, trend and disruptive effects of six prominent accommodation features (view, terrace, pool, shop, location and room).

Findings

Single accommodation features reveal different seasonal patterns. Trend analyses indicate long-term trend effects and short-term disruption effects caused by Covid-19. In contrast, no long-term effect of the pandemic was found.

Practical implications

The findings stress the need to address seasonality at the single accommodation feature level. Beyond targeting specific features at different guest groups, new approaches could allow dynamic price optimization. Real-time insight can be used for the targeted marketing of platform providers and accommodation owners.

Originality/value

A novel application of a time series perspective reveals trends and seasonal changes in travelers’ accommodation feature preferences. The findings help better address travelers’ needs in P2P offerings.

Keywords

Citation

Teichert, T., González-Martel, C., Hernández, J.M. and Schweiggart, N. (2024), "Dynamics in accommodation feature preferences: exploring the use of time series analysis of online reviews for decomposing temporal effects", International Journal of Contemporary Hospitality Management, Vol. 36 No. 7, pp. 2521-2541. https://doi.org/10.1108/IJCHM-03-2023-0279

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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