Question 1
You are recently hired by Corsica Worldwide Holdings as general manager of The Capri, a five-star hotel owned by CWH. The senior management at CWH wants you to assess the hotel’s business and develop a business strategy to reduce cancellations or no-shows. You have been given a tight dateline to draft a business proposal.
There are various reasons for cancellations, including a change in plans, unforeseen scheduling conflicts, or a change of mind. Cancellations have also been easier for customers as hotels usually allow them to cancel their bookings without question free of charge.
Coupled with the development of online booking technologies, customers can now book a room and change their minds later, and this affects booking behaviors among hotel guests.
For any hotel, cancellations can be costly, particularly when done at the last minute, as the hotel may have to resell the canceled rooms at lower rates and incur additional costs for the use of publicity and various distributional channels to sell these rooms.
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Thus, the reduction in cancellations is important to the senior management and your task is to address this issue at The Capri. Understanding the benefits of data-driven decisions, one of the things you set out to do is to analyze the hotel’s booking data.
You want to gain insights into the booking behaviors of your customers, and hopefully, identify where the cancellations are taking place and how to reduce them.
For your analysis, you will create an RMarkdown document and construct your R codes within it. The dataset can be found in ANL501_ECA_hotel.csv. Your response to this question should contain two sections. The first section of your response should contain the heading “Exploratory Data Analysis”.
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Question 2
Before attempting this question, read the handout “Additional-Notes-on-Map Construction.html” contained in Additional-Notes-on-Map Construction.zip to learn how to extract and plot map data from .shp and .geojson files.
Your task is to design the appropriate spatial visualization (s) to shed light on which neighborhoods are the “safest” in Singapore and whether the age profiles of neighborhoods are associated with crime.
For the study, you will use data on five preventable crime cases recorded by the NPCs. The five preventable crimes are robbery, housebreaking, snatch theft, theft of motor vehicles, and outrage of modesty.
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