Prediction Model for Average Daily Rate (ADR) of Bangkok Hotel
Keywords:
Average Daily Rate (ADR), Bangkok hotel, Hedonic price model, Multiple regression analysisAbstract
The main objective of this research was to propose an Average Daily Rate (ADR) prediction model for three to five star hotels in Bangkok using the Hedonic Price Model. The variables included in the model were derived from a literature review and suggested by an expert panel. Factor analysis was adopted to merge highly correlated variables. The data from 461 hotels in Bangkok were acquired from www.agoda.com. The results showed that 11 variables affecting the ADR and the five variables that had the highest regression coefficients were 1) star rating, 2) score of location overview, 3) score of room comfort, 4) score of staff performance and 5) fitness center availability (presence or absence). The log-linear model was selected as it showed the highest Adjusted R2 (Adjusted R2 = 0.843). The observed ADRs and the predicted ADRs from the proposed model were not significantly different, as shown by the pair sample t-test’s value of 0.153 at the 0.05 significant level and 0.472 Theil’s U statistical value. This suggests that the proposed model can be used to provide useful information for Bangkok hotel investors or developers regarding hotel value appraisal, or the pricing of hotel room rates.
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