有用性
声誉
产品(数学)
质量(理念)
集合(抽象数据类型)
背景(考古学)
用户生成的内容
营销
计算机科学
广告
业务
社会化媒体
心理学
万维网
社会学
地理
社会科学
程序设计语言
几何学
认识论
社会心理学
数学
考古
哲学
作者
Raoul V. Kübler,Lara Lobschat,Lina Welke,Hugo van der Meij
标识
DOI:10.1016/j.jretai.2023.09.001
摘要
Online retailing is still dominated by information asymmetries, as it often remains difficult for consumers to fully judge the quality of a product online. Reviews written by customers help to reduce this asymmetry. Helpful reviews have thus become an important tool to drive online sales. Beside textual information, reviews nowadays also often include images that can further help consumers to better judge products or services. While online retailers need to invest substantial resources in hosting and incentivizing review images, it remains unclear under which conditions review images drive (or reduce) review helpfulness and how review image content affects review helpfulness. We rely on a set of more than 97,000 reviews from Amazon to investigate the contingencies under which review images increase review helpfulness. Furthermore, we rely on more than 6,000 images in our data set to explore how review image content (i.e., image focus and context fit) drives review helpfulness. Our results show that online retailers should especially motivate consumers to include images in a review when the overall rating is extremely positive, when the reviewer has a high reputation, and when the review addresses a hedonic or experience product. Our image content analysis further shows that images help to increase helpfulness when they show the product in application. This effect is especially strong in the case of longer reviews.
科研通智能强力驱动
Strongly Powered by AbleSci AI