The impact of service attributes and category on eWOM helpfulness: An investigation of extremely negative and positive ratings using latent semantic analytics and regression analysis

R. Filieri (), F. Galati and E. Raguseo
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R. Filieri: Audencia Business School

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Abstract: Online reviews have become irreplaceable product/service information for many consumers. However, not all consumer reviews are deemed to be helpful. Drawing upon expectation-confirmation theory and the attribute-based model of consumer decision-making, this study investigates the role of service attributes and the moderating role of service category in the prediction of extremely positive and extremely negative ratings helpfulness. This study uses latent semantic analysis and regression analysis using a sample of 490 extremely negative and 3757 extremely positive ratings of hotels from TripAdvisor.com. Results show that some product attributes discussed in consumer reviews are particularly important in the determination of the helpfulness of consumer reviews associated with extreme ratings. Findings also suggest the moderating role of service category (i.e. hotel stars) in the relationship between hotel attributes and extreme ratings helpfulness. This study stresses the importance of service attributes and classification in the evaluation of extremely positive and extremely negative ratings helpfulness. Theoretical and managerial implications are discussed.

Keywords: eWOM; Extreme ratings; Review helpfulness; Hotel attributes; Hotel category; Text analytics (search for similar items in EconPapers)
Date: 2020-12
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Published in Computers in Human Behavior, 2020, ⟨https://doi.org/10.1016/j.chb.2020.106527⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04713690

DOI: 10.1016/j.chb.2020.106527

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