Do hotels with higher guest ratings have higher room prices?
[Booking.com ask guests to give a score between 1 to 10 based on each of following items (services) of the hotels: cleanliness, comfort, location, facilities, staff and value for money]
Figure 1a : Resort room prices and guest ratings, Maldives Jan-August 2021
Figure 1b : Resort room prices and guest ratings, Feb2021
Figures 1a and 1b above suggest that resort room prices in the Maldives increase with higher guest ratings, suggesting tourists are willing to pay (WTP) higher prices to higher quality of the tourism products. Some researchers (Rigall-I-Torrent and Fluvià ,2011), use rating as an explanatory variable in regressions of hotel room price. They claim that rating indicates quality factors such as aesthetic or visual beauty that are not captured by the observed variables.
Figure 2a : Guesthouse room prices and guest ratings, Maldives Jan-August 2021
In the guesthouse segment, however, Figure 2a does not indicate a clear relationship between the two variables. And when we have a closer look at the guesthouse data for Feb2021 (see Figure 2b), it suggests that room price increases with the rating until a score of 8.7, and after that, even with the low price, guests tend to give a higher rating to the hotel.
What does this observation suggests?
After ignoring few outliers, observation suggests that there is a limitation on the quality of the products in the guesthouse segment. In other words, tourists would still give a higher rating if their service matches the price they paid (value for money).
It is also likely that rating is endogenous. Price and rating would be affected by the same unobservable characteristics internal or external to hotels.
Figure 2b : Guesthouse room prices and guest ratings, Feb2021
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R code
# File: Analysis_tdp_data2021_a1.R
# Author: Dr. Ibarhaim Zuhuree, phd14403@grips.ac.jp
# Date: 15Aug2021
# Updated 25 Aug2021 —- many thanks to Dr. Zahir for his contribution to the dataset
# relevant packages
#install.packages(“tidyverse”)
library(tidyverse)
library(readr)
library(dplyr)
library(stringr)
##Load tables needed for analysis
load(“~/tdp_data2021_c1.RData”)
###Do hotels closer to beach has higher room price than hotels far away?
### BASIC ggplots #########################################
#room price and guest rating of the resort segment in the Maldives
ggplot(data = resortp_data2021_c1) + # has full dataset for resorts
geom_point(mapping = aes(x = gRating, y = rPrice, color = r_location)) +
facet_wrap(~ r_location, nrow = 2)
resortp_data2021_a1 <- resortp_data2021_c1 %>%
filter(rPrice<5000 & month==2 & gRating!=10 & r_location!=”sea view”)
ggplot(data = resortp_data2021_a1) +
geom_smooth(mapping = aes(x = gRating, y = rPrice, color = r_location))
##guesthouse segment
ghp_data2021_a1 <- ghp_data2021_c1 %>%
filter(rPrice<250 & r_people==”double”) # filtered
ggplot(data = ghp_data2021_a1) + # has full dataset for guesthouses
geom_point(mapping = aes(x = gRating, y = rPrice, color = r_class)) +
facet_wrap(~ r_class, nrow = 2)
ghp_data2021_a1 <- ghp_data2021_c1 %>%
filter(rPrice<250 & r_people==”double” & month==2 & r_class!=”other”)
ggplot(data = ghp_data2021_a1) + # for gh
geom_smooth(mapping = aes(x = gRating, y = rPrice, color = r_class))