Step 1: Find the Optimal Pricing Strategy for Each Scenario
In a particular scenario, if we set the prices for Airbus and Boeing to a particular level, the cashflow analysis in the spreadsheet will tell us the NPV associated with that set of prices. Unfortunately, if we change the prices, the NPVs will change. Before we can put the NPVs of a particular scenario into a game cell, we need to know the correct (optimal) prices for that scenario. You can think of this as a two-stage game. In the first stage, the firms choose whether to enter. In the second stage, they choose their optimal prices to compete in the chosen competitive environment. To set up and solve the entry game, we first must find the prices that maximize NPV for each firm at the same time. These prices are the solution to the differentiated Bertrand oligopoly problem.
As you learned in the spreadsheet exercise on “Profits and Rivalry,” the equilibrium choice of decision variables (quantities in the Cournot oligopoly and prices in the Bertrand oligopoly) happens where the reaction functions cross. You also saw that because reaction functions converge, you can find the equilibrium by using “Solver” to iteratively find the optimal price of each firm in response to the optimal price of the other firm. In this particular project, set the price of Boeing and Airbus at a particular level and use Solver to find the price for Airbus that will maximize Airbus’ NPV given the preset level of Boeing’s price. Then use Solver to find the optimal price for Boeing that will maximize Boeing’s NPV given the previously optimized price for Airbus. Then find Airbus best response to Boeing and so on. Continue until the prices reach the equilibrium level – they will stop changing in response to the other. In this particular case, the reaction functions are very steep and will converge in four or less iterations of Solver. Warning: You must set the starting prices for each firm such that both firms have market share greater than zero. If either firm has zero market share, Solver will fail.
You then need to find a similar pricing equilibrium for the other scenarios. However, if you think about it, you don't have to go through this procedure where Airbus doesn't launch. Under those scenarios, Boeing is a monopolist (even when Boeing doesn’t launch it still has the 747) and Airbus earns an NPV of zero. Boeing's payoff can be determined simply by finding the price for Boeing that maximizes NPV.
Step 2: Assemble the Payoff Matrix and Determine the Outcome of the Game
Once you have the payoffs for both Airbus and Boeing under each scenario, you can put those payoffs into a game matrix similar to the ones done in class. An example appears in the first worksheet of the spreadsheet assignment. Using the same principles described in that handout, you can then determine the likely outcome of this strategic interaction between Airbus and Boeing.
Game Theoretic Principles in This Analysis
A key insight from game theory that can be applied to strategic reasoning in business situations is the principle, "Look forward, and reason back." This principle refers to the idea that when attempting to determine what your course of action should be in a given situation, it is important that you consider the potential responses a competitor may use. If you can anticipate how a competitor is likely to react in a situation, you can pick your actions contingent on those potential responses, thus, improving your performance.
Throughout this quantitative analysis of Airbus vs. Boeing, you have been applying the principle, "Look forward, reason back." When you account for the pricing strategy used by Boeing when determining Airbus' pricing strategy, you are applying this principle. When you consider the outcomes of the pricing competition between Airbus and Boeing while deciding whether to launch a new jumbo jet, you are once again making use of this important principle. When you attempt to figure out whether Airbus should launch the A3XX based on Boeing's potential responses to Airbus' strategy, once again you are "looking forward (to Boeing's response), and reasoning back (to figure out what Airbus should do)." Thus, this fundamental principle is nested throughout the analysis.
Exercising Judgement in the Use of Quantitative Analysis
The exercise of constructing a quantitative model of a business situation is valuable for a number of reasons. First, the act of formulating a model imposes discipline on your thought process. To get a model to "work," you have to be explicit about your assumptions, how those assumptions interact with one another, and how they affect the outcomes in which you are interested. Second, a model is useful in predicting what the outcomes of a situation will actually be. If you are making an investment in launching a new product or business, you should be interested in determining what the payoff to the company will be. Having an answer to this question is critical to understanding whether the new product is a good investment or not. Finally, a quantitative model of a business situation is important to assessing the risks associated with the investment as well as the sensitivity of the investment to the assumptions underlying your decision-making process. Assessing the risks associated with an investment decision is where analysis and judgement meet, and this is your final task in formulating a recommendation for Airbus and Boeing.
No model is perfect, and a model should not be judged on the basis of whether or not it captures every single detail in the "real world." The important issue is whether or not the model captures the factors that are most relevant in determining outcomes. However, you need to learn how to balance the imperfections of the model against your own personal experience and judgement. Ultimately, this is what managerial decision-making is all about.
Caveats and Risks
So, how do you bring judgement to bear upon these issues? Here, you need to take into account the caveats and risks associated with the model. How reasonable are our projections of total industry demand? What are the risks if that demand does not materialize? What if there are variations in the costs of launching the product? What difference does it make whether or not Airbus is subsidized by the European Governments. Such factors could influence decision-making process, and the importance and likelihood of such events should figure into your recommendations. Incorporating such factors into your thinking is about exercising judgement.
Therefore, after you have run through the analysis, try and think about how the assumptions affect the outcomes you forecast. Would changes in any of these assumptions dramatically affect your decision? What other strategic concerns might Airbus and Boeing have which could override the strategy recommended by the quantitative analysis?
Conclusion
So, there you go; that should get you started! My expectation is that each group will turn in a spreadsheet analysis of the entry decision making explicit your assumptions, your game theoretic analysis, and your recommendation. Given that the spreadsheet is completed, your two biggest tasks will be in determining the best assumptions (you set them in the “Overview” worksheet) and in setting up and solving the entry game. There is a lot of information to help in your making assumptions on the Boeing and Airbus webpages. Links are available on the project webpage.
This can seem like a complex assignment. If you need any further assistance, do not hesitate in contacting me. The quantitative analysis is intended to facilitate, not hamper your analysis. Also, please make sure that everyone is involved. Don't just hand the financial analysis off to one person.
Everything you need to know or consider in formulating your analysis can be found in the case, Airbus A3XX: Developing the World’s Largest Commercial Jet.
The odd-numbered teams should make recommendations regarding Airbus' strategy; the even-numbered teams should concentrate on Boeing.
Thus, you can see that there are four different scenarios: 1) Airbus launches, Boeing doesn't lauch; 2) Airbus launches, Boeing launches; 3) Airbus doesn't launch, Boeing does; and 4) Airbus doesn't launch, and Boeing doesn't either.
If you consider the discrepancies in the projections reported in the case, the "Superjumbo" article, and the market forecast on Boeing's webpage, there would seem to be plenty of uncertainty about what is going to happen.
One aspect of the model that you need to consider in forming your recommendations is the model of demand and market share imbedded in the analysis. So, let's go over that a little bit. Basically, the demand and market share for commercial aircraft and is driven by two factors: the demand for airline transportation (freight and people) and the operational efficiency of new aircraft versus old. Both of these factors are either directly or indirectly reflected in the spreadsheet model. The total level of demand is a function of the average price levels of the firm. So, as the price for aircraft goes up, the expected level of demand goes down. Second, airlines decide whose aircraft they will buy based on who provides the best efficiency advantage. In this model, your market share is equal to the efficiency advantage you provide relative to your competitors. Having this factor included in the model means that Airbus has slightly more pricing flexibility relative to Boeing because the A3XX is 20% more efficient than the Boeing according to case. However, we can assume that such an advantage disappears if Boeing launches a new plane. This leads to another point. The model explicitly assumes that operational efficiency is the only form of differentiation advantage available to Airbus and Boeing, but there are others. For example, we might expect the design of the passenger cabin, etc. would be important to Airbus' and Boeing's customers, the airlines. In addition, Boeing probably has more brand name and reputation capital than Airbus. After all, the 747 has been flying for 30 years with one of the lowest accident records of any aircraft. These are just a few examples of the types of issues you can think about. Obviously, given the space constraints that you face, you can't write about everything, and you need to prioritize your analysis. But, it is good practice to think in pretty broad terms about these issues.
