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

Arghya Ray, Pradip Kumar Bala and Nripendra P. Rana

Journal of Business Research, 2021, vol. 128, issue C, 391-404

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.

Keywords: Brand attitude; Online user-generated content; Online travel agency services; Qualitative aspects; Textual data (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:128:y:2021:i:c:p:391-404

DOI: 10.1016/j.jbusres.2021.02.028

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