Reference no: EM133020039

A research study reported that one in five hotel bookings are canceled before the guest arrives at the hotel. A last-minute cancellation or no-show means the room would be left unoccupied, which results in a loss of revenue for the day. Even if the hotel manages to sell the room again, it would probably be at a much lower rate because it is too near to the check-in date. For a hotel, a high cancellation ratio not only impacts the revenue but also leads to poor marketing and low market share. To improve business, the marketing manager of hotel H would like to learn more about the booking cancellation issue. As a data analyst in the marketing department, you are given a relevant dataset Hotel_Booking_Cancellation.csv, which contains a total of 2,417 hotel booking records. Your job is to help the hotel understand the possible factors that would affect the booking cancellation and assist your manager in evaluating the usefulness of the constructed models for the given problem. The details of the dataset are as following:

(a) Describe the business objective and data mining objective of the given business problem. Appraise whether the Association Rule Mining method is appropriate to study this problem.