| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4972590 | Information & Management | 2017 | 17 Pages |
Abstract
Product reviews have gained much popularity in recent years. This study examines the theoretical foundation of review helpfulness and reports how the interactions among three user-controllable filters together with three groups of predictors affect review helpfulness. Reviews from TripAdvisor.com were analyzed against three analytical models. The results show that these groups of variables have a varying effect on different user-controllable filters. Review rating and number of words are key predictors of helpfulness across all three filters. The recency, frequency, and monetary (RFM) model has received a consistent support across all filters as well. Managerial implications are provided.
Related Topics
Physical Sciences and Engineering
Computer Science
Information Systems
Authors
Ya-Han Hu, Kuanchin Chen, Pei-Ju Lee,