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This study aims to propose a model to explain online review helpfulness grounded on both previously identified constructs (e.g. review length) and new ones, which have been analyzed in other online reviews’ contexts but not to explain helpfulness.

A total of 112,856 reviews published in TripAdvisor about 21 Las Vegas hotels were collected and a random forest model was trained to assess if a review has received a helpful vote or not.

After confirming the validity of the proposed model, each of the constructs was evaluated to assess its contribution to explaining helpfulness. Specifically, a newly proposed construct, the response lag of the manager’s replies to reviews, was among the most relevant constructs.

The achieved results suggest that hoteliers should invest not only in responding to the most interesting reviews from the hotel’s perspective but also that they should do it quickly to increase the likeliness of the review being considered helpful to others.

论：项解释酒店业中在线评论有用性的模型

研究目的：本论文提出一项模型, 用于解释在线网络的有用性, 这项模型基于之前文献定义的结构（如评论长短）以及在其他在线评论题材下分析的新结构。而这些结构之前未用来解释有用性。

研究设计/方法/途径：样本数据为112,856条TripAdvisor关于21家拉斯维加斯酒店的评论。本论文创建了一种随机森林模型, 用于检测是否一条评论是有用的。

研究结果：本论文肯定了提出模型的有效性, 此外, 本论文评估了每个模型结构, 检测其是否解释了有用性。具体地说, 本论文提出了一种新的结构, 经理回复评论的时间长短, 是最相关的结构之一。

研究原创性/价值：研究结果表明, 酒店经理应该不仅从酒店角度出发回复最有意思的评论, 而且要快速回复, 以增加其他用户评价这条评论是否对他人决策的有用性。