The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Ratings lead you to the product, reviews help you clinch it? The mediating role of online review sentiments on product sales
Abstract
It is generally assumed that ratings are a numeric representation of text sentiments and their valences are consistent. This however may not always be true. Using a panel of data on over 4000 books from Amazon.com, we develop a multiple equation model to examine the inter-relationships between ratings, sentiments, and sales. We find that ratings do not have a significant direct impact on sales but have an indirect impact through sentiments. Sentiments, however, have a direct significant impact on sales. Our findings also indicate that the two most accessible types of reviews - most helpful and most recent - play a significant role in determining sales. This suggests that information that is easily accessible and cognitive effort-reducing heuristics play a role in online purchase decisions. This study advances our understanding on the inter-relationship between ratings, sentiments, and sales and sheds insight on the relevance of ratings and sentiments over a sequential decision making process.
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Cited by
Influence of consumer reviews on online purchasing decisions in older and younger adults
von Helversen, B., Abramczuk, K., Kopeć, W., & Nielek, R. (2018) · Decision Support Systems · doi:10.1016/j.dss.2018.05.006 · Cited by 263
Villarroel Ordenes, F., Ludwig, S., de Ruyter, K., Grewal, D., & Wetzels, M. (2017) · Journal of Consumer Research · doi:10.1093/jcr/ucw070 · Cited by 245
Mariani, M. M., & Nambisan, S. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121009 · Cited by 173
Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms
Kokkodis, M., & Lappas, T. (2020) · Information Systems Research · doi:10.1287/isre.2019.0895 · Cited by 48
Online reviews and product sales: the role of review visibility
Alzate, M., Arce-Urriza, M., & Cebollada, J. (2021) · Journal of Theoretical and Applied Electronic Commerce Research · doi:10.3390/jtaer16040038 · Cited by 45
Metadata
- Authors
- Hu, N., Koh, N. S., & Reddy, S. K.
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 57
- Pages
- 42-53
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2029080598
- Cited by
- 406
- References
- 57
- FWCI
- 40.19
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
