Abstract
There is evidence that review ratings affect sales; yet little is known about the drivers of the star ratings from the perspective of the customers who have written them. A person who writes a review touches upon many different aspects of the experience. It is intriguing to explore the underlying topics that motivate customers to provide certain star ratings. Although there have been many studies to predict rating, they are mostly data driven. A marketing perspective and a consumer theory driven approach is still in their infancy. This article aims to fill this gap in the literature, and to explore the topics of reviews and their effects in determining the star ratings of a review. Since review rating influences prospective customers, traffic to the site and ultimately sales, examining the topics that make a customer rate a review in a certain manner is theoretically and managerially important.
| Original language | English |
|---|---|
| Pages (from-to) | 287-302 |
| Number of pages | 16 |
| Journal | Canadian Journal of Administrative Sciences |
| Volume | 41 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2024 |
Keywords
- explanatory model
- multinomial regression
- online review content
- star rating
- text mining
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