Does the number of reviews that your listing is getting on AirBnB affect the actual review score? Does this effect differ between big or small cities in Spain?
We all know the feeling of opening an e-mail that asks you to leave a review on a product that you just bought or a listing that you stayed the night at. But do more reviews lead to a higher review score? Furthermore, this effect is examined at cities in Spain that differ in sizes, such as Malaga compared to the capital Madrid. This code is written in order to find answers to these questions.
The reason for diving into this problem is because review scores are an important factor for customers when they decide which listing to stay at. Hosts want a good review score and some push their guests to leave a review. The issue that arises is that more reviews does not necessarily result into a higher review score. This study is conducted in order to show hosts if they should or should not push their guests for reviews by analyzing the relationship between review score and number of reviews, while taking moderators and control variables into account.
The relationship between the number of reviews and actual review score may be influenced by other variables, which are integrated in the model as moderators. In this study, three moderators are considered:
- The city size which is encoded using dummy variables. Each of the seven cities in Spain falls in either one of three categories; Big, Medium or Small, depending on the number of residents.
- Room type
- Host characteristics. This variable is measured by taking the average of the sum of various different characteristics of the host, which are the response time, response rate, host location and number of host listings.
To run the files Make is needed . The directory works with make which should be run. Also R-studio is needed to run the R-files. First, an overview of the packages used in this study is given:
install.packages("readr")
install.packages("readxl")
install.packages("dplyr")
install.packages("tidyverse")
This study is conducted by project group 2 of the Data Preparation and Workflow Management course of the TISEM department of Tilburg University. The project is done in the fall 2021 version of the course. The project was part of a team project performed by Marketing Analytics master students. Professor Hannes Datta contributed by providing helpful feedback during project feedback meetings.
Team members: Doria Wengting Wang, Inge Oostveen, Ralph Delsing, Paulus Hovens, Wouter Floors