Executive summary
We have analyzed the existing booking policy of TransAtlantic Airlines and identified potential cost saving.
The implementation of the suggested new booking policy would lead to reduction of total expected costs per flight on average by £8,100.
Furthermore, the new policy would increase the predictability of total costs per flight. With 90% confidence new costs will be in a range £750 and £4,800 as compared to the current range of £1,900 to £20,300. The comparative description of the policies is presented in table 1.
Analysis of existing policy quick fix
Base case model
The foundation of current policy is based on the analysis in table 1. We observe that the total costs for both classes are
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Quick look at the summary table helps us identify that the proposed quick fix is the least value destructing policy out of three policies. It has the lowest mean of total costs, the lowest probability of exceeding £10,000 as well as the narrowest range of the cost.
To be more assured, we have additionally conducted probability dominance analysis (figure 2), which tells that both current and quick fix policy have deterministic dominance (always better) then no overbooking policy (green line). Whereas the quick fix (blue line) has stochastic dominance over currently employed policy (red line). The outcome of current policy maybe occasionally better than our proposed solution, but in the majority of cases the quick fix policy will be better.
Figure 2 Probability dominance analysis
Policy optimization
In order to identify the optimal booking policy we have conducted simulation with 40 different booking levels for business and economy. As these two variables are independent, we have conducted consequential analysis. Results for business class level booking are in (figure 3). The detailed information about tested values is in Appendix B.
Figure 3 Optimal booking policy
We have observed that the lowest expected value of total costs is achieved at 427 and 133 accepted reservations for economy and business respectively. The comparison of current policy against new policy can be found in table
A $2 increase on admission prices has the potential to increase revenues with a low risk of profit loss. A loss would only occur if the price change were to lose more than 572 visitors. An increase to $14 a ticket will bring in extra profits and still remains below the competitors and the ROM’s regular hours
The airline industry has long attempted to segment the air travel market in order to effectively target its constituents. The classic airline model consists of First Class, Business Class and Economy, and the demographics that make up the classes have both similarities and differences to the other classes. For instance there may be similarities between business class travellers on a particular flight, but they will not all be travelling for the same reason. An almost-universal characteristic of air travel is that customers do not fly for the sake of flying; the destination is the important element and the travel is a by-product, a means-to-an-end that involves the necessity of an aircraft that gets the customer from point A to point B.
147 (1) Assume that BlueSky purchases three identical aircraft. How many coach seats should BlueSky order for the three new aircraft? (2) Now suppose that the three aircraft can be different sizes, between 240 and 380 coach seats. (a) How do you think the three aircraft should be allocated among the six routes? In other words, should the same aircraft always fly the same routes? Why or why not? (Hint: You do not need an optimization model to answer this question). (b) How many coach seats should BlueSky order for each of the three new aircraft? (3) Because it is cheaper to manufacture three identical planes, Airbus is offering BlueSky a one-time, $5 million discount if it will order three identical aircraft. Should BlueSky take the discount? In deciding this, you may assume that BlueSky operates 3 banks per weekday through Houston, and that the revenues and demands for every bank on every weekday are equal to the demands in Tables 1 and 2 of the (A) Case.
The purpose of this memorandum is to address the profitability issues at Continental Airlines and to estimate the costs for 2009 to forecast the future outlook of the company. To address these issues, I used regression analysis to observe what effect the 11% reduction in flying capacity would have on the firm’s future operating costs. I also used the results from the regression analysis to verify the costs that, if reduced, would further comply with the implementation of cost-cutting initiatives and operational efficiencies that the company is striving for. Lastly, I consolidated the data to forecast Continental’s financial outlook for 2009, then provided insight
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Jerome Simelane, the airline's Commercial GM, “By using what we have learned over the years about international airline best practice‚ we have also created a cost structure which allows us to offer competitive fares without cutting any corners on quality‚ safety and reliability."
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