Please answer the questions below. Be specific on the arrival
day and the length of stay that you want to apply.
9/20 Wed
9/21 Thu
9/22 Fri
9/23 Sat
9/24 Sun
9/25 Mon
9/26 Tue
Forecasted occupancy %
65
60
90
100
70
85
62
You want to offer huge discounts for 9/20 and 9/21 to bring up
the occupancy, but you also want to reserve the inventory on 9/22
and 9/23 so you can increase the price later. What stay controls
can you use for this purpose? Please provide at least two stay
control options.
How can you bring up the occupancy on 9/21? Will setting up a minimum
two-night stay from 9/20 help to bring up the occupancy on 9/21? If
yes, why? If not, why?
How can you bring up the occupancy on 9/24? Please provide at
least two options.
How can you use the full pattern length of stay in this
scenario for the following two days? Please provide full pattern
solutions and explain how your solution can help to protect high
occupancy day(s) and at the same time bring up low occupancy
day(s).
For arrival on 9/22, your solution is _________
For arrival on 9/21, your solution is _________
What is the best combination of stay controls for each of the
following days in this week if you aim to bring all 7 days to high
occupancy (e.g., above 80% occupancy for each day)?
You need to consider whether your stay
controls are feasible from the customers' point of view. Think
about this week in terms of football guests, career day guests, and
others (transient business).
9/23:
9/22:
9/21:
9/20:
9/25:
Use the information below to calculate
overbooking ratio and use it with the historical no-show data to
decide the number of rooms to overbook on Sundays
Sunday No-show Record
Date
No. of
No-show
Date
No.
of
No-show
Date
No.
of
No-show
Jan-03
2
Mar-13
1
May-22
3
Jan-10
1
Mar-20
3
May-29
2
Jan-17
4
Mar-27
1
Jun-05
0
Jan-24
0
Apr-03
1
Jun-12
1
Jan-31
3
Apr-10
1
Jun-19
3
Feb-07
2
Apr-17
1
Jun-26
2
Feb-14
2
Apr-24
1
Jul-03
2
Feb-21
0
May-01
1
Jul-10
4
Feb-28
3
May-08
1
Jul-17
1
Mar-06
1
May-15
1
Jul-24
0
Sunday No-Shows Distribution Table
No. of No-show
Count
%
No. of No-show
Cumulative %
0
1
2
3
4
Total
Calculate the overbooking ratio.
Use historical data to complete the no-show distribution
table.
Identify the first cumulative probability that is the same or
larger than the overbooking ratio.
Identify the number of rooms to overbook.