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Mapping hotel brand positioning and competitive landscapes by text-mining user-generated content
Hu, F.
Hu, F.
Publication Date
2020-01
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© 2019 Elsevier Ltd. All rights reserved. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
05/06/2019
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Abstract
This study uncovers hotel brand positioning and competitive landscape mapping by text-mining user-generated content (UGC). Rather than relying on a single dimension of consumer evaluation, the current study detects brand attributes by using both customer preferences as well as perceptual performance to develop meaningful insights. For this, the study combines content analysis and repertory grid analysis (RGA) to answer three key research issues. 111,986 hotel reviews from two biggest Chinese cities are used to explore and visualize the competitive landscape of six selected hotel brands across three hotel categories. Findings from the study will not only advance the existing literature on brand positioning and competitive landscape mapping but also help practitioners in developing brand positioning strategies to fight competitors within and across hotel categories.
Version
Accepted manuscript
Citation
Hu F and Trivedi R (2020) Mapping hotel brand positioning and competitive landscapes by text-mining user-generated content. International Journal of Hospitality Management. 84: 102317.
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Article