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Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach

Ray, A.
; 
Bala, P.K.
; 
Rana, Nripendra P.
Publication Date
2021-05
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Keywords
Brand attitude, Online user-generated content, Online travel agency services, Qualitative aspects, Textual data
Rights
© 2021 Elsevier. 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 (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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Yes
Open Access status
openAccess
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Management and Law Publications
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Abstract
This paper aims to explore the important qualitative aspects of online user-generated-content that reflects customers’ brand-attitudes. Additionally, the qualitative aspects can help service-providers understand customers’ brand-attitudes by focusing on the important aspects rather than reading the entire review, which will save both their time and effort. We have utilised a total of 10,000 reviews from TripAdvisor (an online-travel-agency provider). This study has analysed the data using statistical-technique (logistic regression), predictive-model (artificial-neural-networks) and structural-modelling technique to understand the most important aspects (i.e. sentiment, emotion or parts-of-speech) that can help to predict customers’ brand-attitudes. Results show that sentiment is the most important aspect in predicting brand-attitudes. While total sentiment content and content polarity have significant positive association, negative high-arousal emotions and low-arousal emotions have significant negative association with customers’ brand attitudes. However, parts-of-speech aspects have no significant impact on brand attitude. The paper concludes with implications, limitations and future research directions.
URI
http://hdl.handle.net/10454/18339
Version
Accepted manuscript
Citation
Ray A, Bala PK and Rana NP (2021) Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach. Journal of Business Research. 128: 391-404.
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Link to published version
Link to Version of Record
https://doi.org/10.1016/j.jbusres.2021.02.028
Type
Article
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