Airbnb Case Discussion

2 Running head: C207 Task 2 A. As Identified in Task 1, a hotel owner would like to evaluate his cancellation policies based on two hotel styles. One is a resort style hotel, and the other is a city hotel. The owner has noticed many cancellations in the past few months and would like to see if there is any major difference in the number of cancellations between the two hotel styles. If there are more cancelations at one of the locations, then there will be a new cancellation policy put in place to ensure no money is lost when cancellations take place. Since it is unfavorable to have these cancelation policies, the owner would only like to add a new policy to one hotel (the one with the most cancellations). In this scenario the appropriate question to be analyzed is, “Are there more cancellations at a resort hotel or a city hotel?” B1 & B2. To answer this question, 30 reservations from the resort hotel will be gathered, and 30 reservations from the city hotel will be collected as well. These will show how many cancelations there were within the 30 reservations collected, and then compare the sample set averages to each other in order to determine which hotel has the most cancellations. This data collection has been recorded in excel on a spreadsheet in order to create the following chart: Hotel cancellations out of 60 Reservations 30.00% City Hotel Resort Hotel 70.00% 3 Running head: C207 Task 2 C1. In order to test the data that has been collected there must be a statistical analysis performed on the data sets. For the business question being asked, l will use the Chi-square analysis technique. This will show if there are significant differences in the frequency of cancellations among the two hotels, which I am testing against each other. This will allow me to accept or reject my null hypothesis. C2. Output and Calculations 4 Running head: C207 Task 2 C3. I chose the two-way Chi-square test as my analysis technique. I did this because Chi square is used to test if there f7are significant differences among categorical data. My categories are mutually exclusive and may be used for inference when random sampling. A twoway test was appropriate instead of the one-way Chi-square test because there is more than one variable in question. This test will show if there is a statistically significant result which will clearly determine if the null hypothesis should be rejected or not. D1. For the analysis, the question being asked is if there are more cancellations at a city hotel or a resort hotel. If I analyze the data from my Chi-Square test, it shows that I am 1 degree from freedom and my chi square statistic X2 is 4.8. I am testing my null hypothesis that the data sets are equal to each other (no significant difference), and then the outputs from my test will allow me to accept or reject my null hypothesis. The Chi square test shows that the p-value is . 02, which means the p value is less than .05. This means that I will reject the null hypothesis. This shows statistically that there is a significant difference in the data set, and the City hotel has more cancellations than the resort hotel. D2. This data analysis has some limitations. There were some variables that were not tested for in the sample data that could also affect cancelations. These include the month of cancellations, weather, price of rooms that were cancelled, or any rooms booked for cancelled events. Any of the variables that the sample data did not test for has the ability to skew the data 5 Running head: C207 Task 2 and conclude it to be useless. In a more general sense, the data was able to still provide a clear picture and allow the hotel owner to make decisions moving forward based on the results. D3. My recommended course of action moving forward would be to accept the results of this analysis and make policies that coincide with that. This means I believe that the hotel owner should put in place a Cancellation policy immediately for the city hotel. The policy should include a cancellation fee that will be charged if the guest cancels. This way the hotel is not losing money due to a significant number of cancelations. The resort hotel did not show as many cancelations and at this time does not need a policy in place.