Abstract This research aims to propose a prediction model for the Average Daily Rate (ADR) for Bangkok four-star hotels. The model was developed using the hedonic price model, which was calculated from 158 four-star hotels in Bangkok. The variables in the model were derived from a literature review and suggested by an expert panel. Factor Analysis was adopted to merge the highly correlated variables. The best-fit model is a log-linear form with a .576 Adjusted R2 value. The top five most sensitive variables are (1) staff performance score from Agoda’s review, (2) location score from Agoda’s review, (3) room standard score from Agoda’s review, (4) fitness availability (presence or absence), and (5) the number of hotel outlets. The model was verified by a paired-sample t-test from 30 hotels with similar criteria. From the analysis, the observed ADRs were not significantly different from the predicted ADRs at the .05 significance level (p-value = .849). Furthermore, Theil’s U statistic was .578, which could suggest that the model has high accuracy. In summary, this model can give useful information to investors or developers in the decision-making process for hotel investment, hotel renovation, hotel room pricing, and rechecking the ADRs of operating hotels.

中文翻译：

---

曼谷四星级酒店的平均每日房价（ADR）预测模型

摘要本研究旨在为曼谷四星级酒店的平均每日房价（ADR）提出预测模型。该模型是使用享乐价格模型开发的，该模型是根据曼谷158家四星级酒店计算得出的。该模型中的变量来自文献综述，并由专家小组建议。采用因子分析来合并高度相关的变量。最佳拟合模型是对数线性形式，调整后的R2值为.576。最敏感的五个变量是（1）Agoda的工作人员绩效得分，（2）Agoda的工作位置得分，（3）Agoda的房间标准得分，（4）健身状况（有无）和（5） ）酒店网点数量。该模型已通过来自30家具有类似标准的酒店的配对样本t检验进行了验证。根据分析，在0.05的显着性水平（p值= .849）下，观察到的ADR与预测的ADR没有显着差异。此外，Theil的U统计量是.578，这可能表明该模型具有较高的准确性。总之，该模型可以在酒店投资，酒店装修，酒店客房定价以及重新检查运营酒店的ADR的决策过程中为投资者或开发商提供有用的信息。