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Spreadsheet for case UV6293

In this, the second of a two-case decision analysis series, an entrepreneur must decide whether there are additional benefits from operating in more than one U.S. city. He explores the business model of operating local production facilities in major cities, metro areas with a population of over one million. Going national in year three would allow for a year four launch. Again, the entrepreneur must choose between a discounted and a premium strategy. He must also consider how the U.S. national florists might react to whatever strategy he chooses. Student spreadsheets are available for both the A and the B cases.

This case was awarded first place in the INFORMS 2011 case competition. A seasoned Internet retailing entrepreneur considers starting a national floral delivery service to compete with the major U.S. players. Decisions include whether to open a production facility in a single city and begin to deliver there? Which strategy should he use to decide-a premium or a discounted strategy? Ideal for MBA and undergraduate students in decision analysis modules or courses, this case offers an optional student spreadsheet useful for considering different strategies and calculating the resulting net present value of the opportunity. A B case with a spreadsheet is also available.

A small start-up company must make additional investments to maximize its firm value. But the company owner will not make this investment unless she can renegotiate outstanding debt claims. Solving this "debt overhang" problem through negotiation is the focus of the case. In this context, students are exposed to a variety of issues: the nature of financial claims, bargaining and negotiation fundamentals, and agency costs of debt.

The B case brings Intrinergy's point of view into play. Intrinergy has two options for obtaining the biomass to produce steam for the industrial plant. They can use wood chips or sawdust. The wood chips are available at woodlands, essentially for free, although a capital investment in trucks is needed to bring the chips to the plant, and there is variable cost to chip the waste wood and transporting it to the steam plant. Sawdust is delivered to the plant at a price that follows a random walk. Once again a Monte Carlo simulation is needed to compare the alternatives. How Intrinergy fuels the steam plant does not matter to BurMills and will not change BurMills decision. On the other hand, it will matter to Intrinergy which option BurMills takes, since it affects the level and risk of the revenue to Intrinergy from the project. (A student spreadsheet is available for use with the case.

Spreadsheet supplement to case UV4312.

The A case describes the decision the BurMills textile company will make regarding whether to change from producing their own steam to outsourcing their steam production to Intrinergy. BurMills can calculate the present value of cost flows for three alternatives: producing their own steam from burning natural gas, outsourcing to Intrinergy with either a fixed price contract, or with a price contract that floats with the natural gas price at Henry Hub. In addition to the standard costs associated with steam production the case adds depth by providing the possibility of revenue from carbon credits. These credits are earned because the energy in the Intrinergy plant is created from biomass. A proper analysis will include a Monte Carlo simulation based on an arithmetic random walk for carbon credit pricing, a mean-reverting arithmetic random walk for Henry Hub natural gas spot prices, and other distributions. (A student spreadsheet is available to accompany this case.)

Student spreadsheet to cases UV0840 and UV0841.

This case is an excellent illustration of offline/online integration. Office Depot used its supply chain, systems integration, and existing offline channel strengths to overcome competitive online threats from pure Internet players and other office-products-category players. Students get to consider the critical strategic options for overall strategy, pricing, product line, promotion, and business integration.

Set in 1999, this case allows students to put themselves in the positions of both Airbus and Boeing as Boeing considered how to respond to Airbus's decision to announce its plans to proceed or not with the $10 billion development of the world's first commercial superjumbo jet, the Airbus A3XX. Boeing was considering a development effort to "stretch" its 747 jumbo jet into a larger superjumbo version, the 747-X. At the time, the two companies' widely available 20-year forecasts for jumbo- and superjumbo-jet demand were particularly divergent. In light of this very public "agreement to disagree," Boeing could pursue several alternatives, all of which were related to Airbus's decision about whether or not to develop the A3XX. This case presents an opportunity for students to make a real downstream decision. It was prepared as a final exam for an introductory decision analysis course involving subjective probability assessment, decision tree modeling, simulation, real options, and game theory. In the analysis of this case, a student is expected to utilize ideas from all five of these areas.

Spreadsheet supplement for case UV1302.

This case is intended to work well as an exam or a capstone for a course on decision analysis, simulation, real options, and game theory. It explores a conventional snack-chip marketer's strategy in China for promoting and advertising a recently acquired healthy snack-chip brand in mid-2002. The marketer has some key decisions to make, now and in the future, about a range of marketing expenditures in the context of an exciting emerging market and in the face of a formidable competitive threat from its chief rival. The case allows students to consider how two parties' decisions about marketing expenditures and market entry interact and to extend the notion of a single party's downstream decision (or real option) to multiple parties' "interactive" real options. The case's competitive situation can be modeled as a dynamic game of imperfect information, or a multiperiod decision situation with continuous uncertainties and a strategic interaction embedded downstream. Monte Carlo simulation of both parties' payoffs under equilibrium play in the downstream subgame yields a subgame perfect Nash equilibrium, which entails "interactive" threshold policies for both parties.

Spreadsheet for case UV1312

Spreadsheet supplement to cases UV0840 and UV0841.

The organizers of a music festival may use video from the Friday concert to create a DVD to sell to those who come to the Saturday concert. Attendance on Saturday is uncertain, as is the percentage of those who attend on Saturday who will buy the DVD. Is this a good project? If so, what number of DVDs should be burned early Saturday morning and offered for sale at that evening's performance? By that time, Friday attendance is known, as well as whether it rained on Friday, and there is a forecast for whether it will rain on Saturday. Historical information on these variables may help us predict Saturday attendance using multiple regression; together with the results of a marketing survey, such analysis will help us make better purchasing decisions. This case series (see also the A case, UV0840) can be used to illuminate a multitude of concepts that are covered in basic decision-analysis courses. The series starts by examining the role of uncertainty in decision making, proceeds through the estimation of probability distributions from sample data with multiple regression, culminates in the development of a full decision model, and ends with a qualitative and quantitative analysis (with a tornado diagram) of how to add value and reduce risk. Key pitfalls for students are failing to recognize both limits on sales (supply and demand), incomplete reasoning in the determination of the attendance probability distribution, and oversimplifying the full forecast model (i.e., averaging the Saturday rain/no Saturday rain outcomes, rather than incorporating the uncertainty explicitly into the simulation).

The organizers of a music festival may use video from the Friday concert to create a DVD to sell to those who come to the Saturday concert. Attendance on Saturday is uncertain, as is the percentage of those who attend on Saturday who will buy the DVD. Is this a good project? If so, what number of DVDs should be burned early Saturday morning and offered for sale at that evening's performance? By that time, Friday attendance is known, as well as whether it rained on Friday, and there is a forecast for whether it will rain on Saturday. Historical information on these variables may help us predict Saturday attendance using multiple regression; together with the results of a marketing survey, such analysis will help us make better purchasing decisions. This case series (see also the B case, UV0841) can be used to illuminate a multitude of concepts that are covered in basic decision-analysis courses. The series starts by examining the role of uncertainty in decision making, proceeds through the estimation of probability distributions from sample data with multiple regression, culminates in the development of a full decision model, and ends with a qualitative and quantitative analysis (with a tornado diagram) of how to add value and reduce risk. Key pitfalls for students are failing to recognize both limits on sales (supply and demand), incomplete reasoning in the determination of the attendance probability distribution, and oversimplifying the full forecast model (i.e., averaging the Saturday rain/no Saturday rain outcomes, rather than incorporating the uncertainty explicitly into the simulation).

These three caselets provide practice using risk preference and utility, with both exponential utility (constant risk aversion) and logarithmic utility (decreasing risk aversion). The second caselet is an extension of "Integrated Siting Systems, Inc." (UV0355). Students may use TreePlan to conduct a sensitivity analysis of risk tolerance, and can employ Solver to find optimal risk sharing. Students will learn concepts and garner insights regarding portfolio risk in making investments, how intangibles can affect evaluation of risk, and how expected utility can exploit risk sharing.

The task is to prepare a sealed bid against one opponent for a hotel that has an appraised value and a specific, higher value for a company. There is data about the ratio of bids of the other bidder to the appraised value in similar sealed bids. Students will learn to give up many unfounded notions of how to bid and to develop a strategic approach to finding the best bid.

This comprehensive technical note explains linear regression. It is intended for students with no prior knowlede of the topic. It is devided into nine sections, which may be assigned separately: 1. The simple linear model, 2. Fitting the model using least Squares, 3. Important properties of the least-squares regression line, 4. Summary regression statistics, 5. Assumptions behind the linear model, 6. Model-building Philosophy, 7. Forecasting using the linear model, 8. Using dummy variables to represent categorical variables, and 9. Useful data transformations. The sections correspond to stand-alone notes also available through Darden Business Publishing

Spreadsheet for case UV6187