Purpose

This study aims to investigate the promoting effects of the quantity and quality of online review user-generated photos (UGPs) on perceived review usefulness. The research further tests the hindering effect of human facial presence in review photos on review usefulness.

Design/methodology/approach

Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling.

Findings

Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has positive impacts on perceived review usefulness. The quality of online review UGPs can also enhance perceived review usefulness, whereas facial presence in these UGPs hinders perceived review usefulness.

Practical implications

Findings suggest that practitioners can implement certain tactics to potentially improve consumers’ willingness to share more UGPs and UGPs with higher quality. Review websites could develop image-processing algorithms for identifying and presenting UGPs containing core attributes in prominent positions on the site.

Originality/value

To the best of the authors’ knowledge, this study is the first to present a comprehensive analytical framework investigating the enhancing or hindering roles of review photo quantity, photo quality and facial presence in online review UGPs on review usefulness. Using the heuristic-systematic model as a theoretical foundation, this study verifies the additivity effect and attenuation effect of UGPs’ visual elements on judgements of online review usefulness. Furthermore, it extends scalable image data analysis by adopting a deep transfer learning algorithm in hospitality and tourism.

中文翻译：

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信息增强还是阻碍？揭示用户生成的照片对在线评论的影响

目的

本研究旨在调查在线评论用户生成的照片 (UGP) 的数量和质量对感知评论有用性的促进作用。该研究进一步测试了评论照片中人脸的存在对评论有用性的阻碍作用。

设计/方法/途径

本研究以旅游目的地拉斯维加斯的餐馆评论样本为基础，采用了一种结合机器学习算法和计量经济学建模的综合方法。

发现

结果表明，描述餐厅食物、饮料、菜单和物理环境的 UGP 数量对感知评论有用性有积极影响。在线评论 UGP 的质量也可以提高感知评论的有用性，而这些 UGP 中的面部存在会阻碍感知评论的有用性。

实际影响

研究结果表明，从业者可以实施某些策略来潜在地提高消费者分享更多 UGP 和更高质量 UGP 的意愿。评论网站可以开发图像处理算法，用于在网站的显着位置识别和呈现包含核心属性的 UGP。

原创性/价值

据作者所知，本研究首次提出了一个全面的分析框架，调查评论照片数量、照片质量和面部表情在在线评论 UGPs 中对评论有用性的增强或阻碍作用。本研究以启发式-系统模型为理论基础，验证了UGPs视觉元素对在线​​评论有用性判断的加性效应和衰减效应。此外，它通过在酒店和旅游业中采用深度迁移学习算法来扩展可扩展的图像数据分析。