The note provides a qualitative and quantitative overview of the North American airline and airport industries with data covering 2016 to 2020. Specifically, the data covers five airlines—American Airlines Group Inc., Delta Air Lines Inc., Southwest Airlines Co., United Airlines Holdings Inc., Air Canada, and WestJet Airlines Ltd.—and five airports—New York’s LaGuardia, Los Angeles International, Chicago’s O’Hare International, Toronto Pearson International, and Tucson International. The objective is to provide students with a basic understanding of the business and operations of the airline and airport industries.
In 2016, a summer intern at Bombay Hospital Indore, in India, was tasked with evaluating the hospital’s patient discharge process. Two types of insured patients required different discharge processes for the payment of outstanding balances. The intern needed to map the respective processes and project the outcomes of (1) moving from the current two parallel systems to one centralized, or pooled, system; and (2) adding a third staff member to process patient discharges and collect payments. Would these suggested solutions resolve the problem of wait times? Would one be more effective than the other?
In 2017, wait times for kidney transplants in Ontario were getting out of hand. While patients from London Health Sciences Centre’s kidney transplant program in London, Ontario, had a reasonable wait of approximately one year, patients in Toronto's kidney transplant program waited almost four years. In an attempt to improve the overall wait times for all Ontario patients, the provincial Ministry of Health intended to merge the two currently independent programs and create a unified wait-list. Two doctors at London Health Sciences Centre were concerned about the effects of the merger for their patients in London, and asked an analytics specialist to determine the effects of the merger. Would the merger have the adverse outcome they expected for their patients’ wait times?
<p style="color: rgb(197, 183, 131);"><strong> AWARD WINNER - INFORMS Case and Teaching Materials Competition</strong></p><br>Founded in 1972, the Association of Tennis Professionals (ATP) was the governing body of three professional men’s tennis circuits: the ATP World Tour, the ATP Challenger Tour, and the ATP Champions Tour. In addition to the ATP World Tour tournaments, there were four highly coveted and extremely competitive Grand Slam tournaments, one of which was Wimbledon. In 2014, two professional tennis players sought to determine their respective odds of placing first at Wimbledon, by using an understanding of probability, stochastic modelling, and Markov chain application. Both players were ranked outside the top 100 and faced a momentous task.
In 2010, the owner of a small air-passenger firm transports individuals and small groups to remote waterfront regions. The business serves two types of customers: private and public. The private customers can afford to pay more, while the public customers’ budget constraints limit what they can pay. The owner wants to set a single price that will maximize his expected revenue across both customer groups. A constraining factor is the plane’s limited capacity, which means the owner cannot accommodate all requests. In other words, after a flight has been sold out, seats may still be requested by customers who potentially might be willing to pay more. See supplement 9B13E014.
A student is trying to incorporate various analytical tools to assist in selecting National Hockey League (NHL) players for a fantasy hockey pool, using individual player data from the 2006-2009 NHL seasons. The student must come up with a strategy in which 16 players are selected for the 2010 season.
In this supplement to Student Plays Fantasy Hockey (A), the student is faced with an additional constraint regarding the total salary of the players selected. The student must come up with a strategy to select 16 players and not exceed $45 million in total salaries.
The head of Patient Escort Services for Vancouver General Hospital (VGH) had to determine the best approach to improve efficiency of the hospital's porter system. Porters represented a vital part of various hospital processes, facilitating timely flow of patients, equipment and materials throughout the hospital. Recently, VGH had experienced incidents in which the capacity of the porters was insufficient to meet the demands of the hospital and, despite best-efforts at scheduling, these problems remained. The head of Patient Escort Services spent several weeks collecting data to determine where the problems existed, and wondered if his data could provide answers to some critical questions: How well did the current porter schedule meet daily demand? What is the optimum number of porters? The head of Patient Escort Services had one week to submit his report to VGH's board of directors.
This note complements Note on Logistic Regression, product #9B10E005 and Note on Logistic Regression - The Binomial Case, product #9B10E012. The focus of this note is to show how to calculate the associated p-values of the estimated beta coefficients using Microsoft Excel. It also illustrates the procedure based on the example from the Note on Logistic Regression - The Binomial Case.
One of the most basic revenue management problems is how to allocate a fixed capacity to various types of classes of customers so that the total profit is maximized. Using the example of a flight traveling from Toronto to Vancouver, the revenue management problem is to decide, in each period, how much of the realized demand to accept and how much to reserve for the latter classes in order maximize the revenue. The crux of the problem revolves around the trade-off between spoilage and dilution. The author uses various mathematical formulae (including the static model, Littlewood's Two-Class model and n-Class model of expected marginal seat revenue) to model optimal seat-allocation outcomes.
A professor is considering buying a new car and is evaluating two models, one with air conditioning and a comfort package, the other with no extras. The two cars are relatively close in price but still above his initial budget, and he is wondering how much he might be able to negotiate the price. A factor that complicates the matter is that the car with the comfort package has a lower interest rate. The professor therefore needs to understand what the net present value of the difference in the two payment plans is.
Due to continued budget shortfalls the project manager for the Spinal Cord Rehabilitation Program at the Toronto Rehabilitation Institute needed to provide proposals for immediate cost-saving measures. One of these measures included how to schedule the nursing staff. The problem involved meeting certain occupancy target levels while ensuring a minimum number and correct mix of available nurses.