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

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  • Ray, Arghya
  • Bala, Pradip Kumar
  • Rana, Nripendra P.

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.

Suggested Citation

  • Ray, Arghya & Bala, Pradip Kumar & Rana, Nripendra P., 2021. "Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach," Journal of Business Research, Elsevier, vol. 128(C), pages 391-404.
    • Handle: RePEc:eee:jbrese:v:128:y:2021:i:c:p:391-404
    DOI: 10.1016/j.jbusres.2021.02.028
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    Cited by:

    1. Arghya Ray & Lan Ma, 2021. "Operational Changes and Performance Outcomes: Analysis on Hotels of Five Asia–Pacific Countries," International Journal of Global Business and Competitiveness, Springer, vol. 16(1), pages 77-88, December.
    2. Heesup Han & Linda-Heejung Lho & Heekyoung Jung & Antonio Ariza-Montes & Luis Araya-Castillo, 2021. "Social Networking Service as a Marketing Technology Tool and Sustainable Business in the Lodging Industry: Investigating the Difference across Older and Younger Age Groups among Tourists," Sustainability, MDPI, vol. 13(10), pages 1-14, May.
    3. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    4. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    5. Kumar, Avinash & Chakraborty, Shibashish & Bala, Pradip Kumar, 2023. "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).

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