Demand

Date	Requests
2020/3/23	68
2020/3/30	73
2020/4/6	74
2020/4/13	72
2020/4/20	69
2020/4/27	71
2020/5/4	69
2020/5/11	69
2020/5/18	75
2020/5/25	68
2020/6/1	74
2020/6/8	71
2020/6/15	70
2020/6/22	71
2020/6/29	68
2020/7/6	71
2020/7/13	73
2020/7/20	71
2020/7/27	71
2020/8/3	70
2020/8/10	74
2020/8/17	67
2020/8/24	73
2020/8/31	73
2020/9/7	72
2020/9/14	69
2020/9/21	73
2020/9/28	74
2020/10/5	72
2020/10/12	72
2020/10/19	72
2020/10/26	72
2020/11/2	66
2020/11/9	72
2020/11/16	66
2020/11/23	75
2020/11/30	67
2020/12/7	72
2020/12/14	71
2020/12/21	74
2020/12/28	69
2021/1/4	69
2021/1/11	71
2021/1/18	71
2021/1/25	67
2021/2/1	68
2021/2/8	68
2021/2/15	75
2021/2/22	70
2021/3/1	67
2021/3/8	72
2021/3/15	71
2021/3/22	68
2021/3/29	73
2021/4/5	74
2021/4/12	72
2021/4/19	69
2021/4/26	71
2021/5/3	69
2021/5/10	69
2021/5/17	75
2021/5/24	68
2021/5/31	74
2021/6/7	71
2021/6/14	70
2021/6/21	71
2021/6/28	68
2021/7/5	71
2021/7/12	73
2021/7/19	71
2021/7/26	71
2021/8/2	70
2021/8/9	74
2021/8/16	67
2021/8/23	73
2021/8/30	73
2021/9/6	72
2021/9/13	69

Question 2 - Hotel Revenue Management A hotel has 150 rooms with standard queen-size beds and two rates: a full price of $200 and a discount price of $120. To receive the discount price, a customer must purchase the room at least two weeks in advance (this helps to distinguish between leisure travelers, who tend to book early, and business travelers who value the flexibility of booking late). You may assume that if a leisure traveler is not able to get the discount rate, she will choose to book at another hotel. To help make decisions regarding a particular Monday night, the hotel manager has put together a dataset with the demand by business travellers for multiple Mondays. The data set is called "demand.xlsx". a) Compute the mass probability function and the cumulative probability function for the number of business customers requesting a room for a Monday night. b) Use Monte Carlo simulation in MS Excel to determine how many rooms should be protected from sale at a discount price. This number is the protection level for full price rooms. Assume that all unprotected rooms will be booked by leisure travellers at a discount rate. Use MS Excel RAND() function to generate numbers uniformly distributed in the interval [0,1] and then the probability functions from part a) to generate random demand by business travellers. Base your decision on 60 replications and please clearly justify your answer based on the point estimates and confidence intervals associated with the revenues associated with different decision values. Consider a minimum of six decision values. c) Determine the booking limit for discount rooms. d) Suppose that for a short time, the hotel's forecast of business customer demand is biased upward: the forecast is too high and fewer business customers appear, on average. Qualitatively describe in one or two sentences the economic consequences of using the protection level and booking limit derived in parts b) and c). e) Suppose that for a short time, the hotel's forecast of business customer demand is biased downward: the forecast is too low and more business customers appear, on average. Qualitatively describe in one or two sentences the economic consequences of using the protection level and booking limit derived in parts b) and c). f) Now use the critical fractile approach discussed in class and the probability functions from part a) to determine the protection level for full price rooms and the booking limit for discount rooms that maximize the expected revenue for Monday night. Show your computations and explain any differences with respect to your answers to questions b) and c) above. Question 2 - Hotel Revenue Management A hotel has 150 rooms with standard queen-size beds and two rates: a full price of $200 and a discount price of $120. To receive the discount price, a customer must purchase the room at least two weeks in advance (this helps to distinguish between leisure travelers, who tend to book early, and business travelers who value the flexibility of booking late). You may assume that if a leisure traveler is not able to get the discount rate, she will choose to book at another hotel. To help make decisions regarding a particular Monday night, the hotel manager has put together a dataset with the demand by business travellers for multiple Mondays. The data set is called "demand.xlsx". a) Compute the mass probability function and the cumulative probability function for the number of business customers requesting a room for a Monday night. b) Use Monte Carlo simulation in MS Excel to determine how many rooms should be protected from sale at a discount price. This number is the protection level for full price rooms. Assume that all unprotected rooms will be booked by leisure travellers at a discount rate. Use MS Excel RAND() function to generate numbers uniformly distributed in the interval [0,1] and then the probability functions from part a) to generate random demand by business travellers. Base your decision on 60 replications and please clearly justify your answer based on the point estimates and confidence intervals associated with the revenues associated with different decision values. Consider a minimum of six decision values. c) Determine the booking limit for discount rooms. d) Suppose that for a short time, the hotel's forecast of business customer demand is biased upward: the forecast is too high and fewer business customers appear, on average. Qualitatively describe in one or two sentences the economic consequences of using the protection level and booking limit derived in parts b) and c). e) Suppose that for a short time, the hotel's forecast of business customer demand is biased downward: the forecast is too low and more business customers appear, on average. Qualitatively describe in one or two sentences the economic consequences of using the protection level and booking limit derived in parts b) and c). f) Now use the critical fractile approach discussed in class and the probability functions from part a) to determine the protection level for full price rooms and the booking limit for discount rooms that maximize the expected revenue for Monday night. Show your computations and explain any differences with respect to your answers to questions b) and c) above