What makes a hotel review helpful? An information requirement perspective

ABSTRACT

With the dramatic proliferation of online user-generated content (UGC), research has emerged to gain understanding of what makes a review helpful, and how useful knowledge can be filtered from over-loaded UGC. Hospitality literature has widely examined the characteristics of helpful online reviews for identifying the determinants of helpfulness. In contrast, the influence of embedded opinions in reviews on helpfulness voting has rarely been examined. This study investigated the distribution of 28 identified hotel attributes ranging between helpful and not-helpful categories, in 85,963 hotel reviews. The findings suggest that customer information requirements differ according to hotel class. Some attributes are reported as uniquely helpful for a specific hotel class, such as proximity to a station (3-stars), bed and lobby (4-stars), and experience and drinks (5-stars), whereas other attributes apply to multiple groups, such as walking distance (3–4 stars), English fluency (4–5 stars), and front-desk, street-road, taxi, and value (3–5 stars).

摘要

随着在线用户生成内容（UGC）的急剧增长，人们开始研究如何使评论变得有用，以及如何从过载的UGC中过滤有用的知识.酒店文献广泛研究了有帮助的在线评论的特征，以确定帮助的决定因素.相比之下，评论中嵌入的观点对帮助性投票的影响很少被研究.这项研究调查了在85963份酒店评论中，28份被识别的酒店属性在帮助和不帮助类别之间的分布.研究结果显示，顾客资讯需求因酒店类别而异. 据报道，某些属性对特定酒店类别有独特的帮助，例如靠近车站（三星级），床和大厅（四星级），体验和饮料（五星级），而其他属性适用于多个 团体，如步行距离（3-4星），英语流畅（4-5星），前台，街道，出租车和价值（3-5星）.

KEYWORDS:

• Hotel
• user-generated content
• review helpfulness
• information requirements
• text mining

Conflict of Interest

None of the authors has received research grants from any Company toward the submitted manuscript or have any conflict of interest.

Disclosure statement

The authors have no conflicts of interest to disclose.

Additional information

Funding

No funding was provided for this manuscript.