Name
Abstract | ||
|---|---|---|
In the fast-evolving digital era, consumers increasingly rely on others' opinions about a product or service rather than corporations' promotional material. This study analyzed online reviews on Amazon.com to identify review types and key drivers of perceived usefulness of reviews to potential customers for search and experience goods. The study found: (1) reviewers tend to give higher star ratings for a product when they provide positive postings; (2) detailed descriptions, with nouns, verbs, adjectives, and adverbs, significantly impacted reviewers' perceptions for experience goods, while reviewers used more verbs for search goods; and (3) potential customers perceived that both high star ratings and lengthy review postings were more helpful to their purchase decisions. The results indicate that it is necessary to: (1) quantify online reviews, (2) develop review platforms according to the nature of products/services, and (3) facilitate the use of multi-/cross-platforms for online reviews by customers to increase their influence on potential customers. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1080/08874417.2016.1275954 | JOURNAL OF COMPUTER INFORMATION SYSTEMS |
Keywords | Field | DocType |
Online review,star rating,type of product,potential customer,Amazon.com | Advertising,Computer science,Noun,Amazon rainforest,Perception,Marketing | Journal |
Volume | Issue | ISSN |
58.0 | 4.0 | 0887-4417 |
Citations | PageRank | References |
2 | 0.37 | 28 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang-Gun Lee | 1 | 247 | 14.15 |
| Silvana Trimi | 2 | 424 | 25.68 |
| Changgyu Yang | 3 | 19 | 3.44 |