Case studies

In 2007, Best Buy was the leading electronics retailer in the United States with more than 941 stores, revenue totaling $31 billion, and a market cap of $21 billion. In 2005, Best Buy had adopted a new business model, culture, and customer-segmentation template called Customer Centricity. This move created volatility in the price of Best Buy stock because of the higher-than-expected employee costs that went with this new way of doing business and the difficulty of executing the old and the new business models simultaneously while the new model was rolled out. Best Buy responded to Wall Street's short-term focus in a myriad of ways. It first asked for investor patience, and stressed the strong operating results achieved in Best Buy stores operating under the new model. But in June 2007, after the stock dropped again, the CEO knew he had to decide whether to open more Best Buy stores, increase the company's dividend, or increase the stock-repurchase program.

This short case could be handed out at the end of class discussion on “J&L Railroad” [UVA-F-1053] in preparation for the following class, or if students are more experienced with hedging and option pricing, the instructor may choose to cover both cases in a single class period. It is the companion case to “J&L Railroad” [UVA-F-1053], and presents more technical issues regarding the hedging problem by requiring students to understand option-pricing principles. The board likes the CFO's hedging recommendations, but it wants a more careful analysis of the bank's prices for its risk-management products: the caps and floors. Besides demanding an understanding of option pricing, this case puts particular emphasis on the calculation and use of implied volatility.

The Home Depot case is a great story. It's about entrepreneurship, growth, CEO leadership, and the dramatic impact, good and bad, a CEO can have on a company's growth culture, strategy, and performance. Home Depot had faced market growth challenges for the last seven years as it tried in numerous ways to reignite its growth engine. The case explores the growth strategies of CEOs Bernie Marcus, Arthur Blank, and Blank's successor Bob Nardelli, a former GE executive. After examining Home Depot's growth history, the case challenges students to devise a growth strategy for the company under a new CEO.

Tiffany & Company was the leading U.S. luxury jewelry brand, generating more than $2.6 billion in revenue through 167 retail outlets globally and from catalogue and Internet sales. For nearly 170 years, Tiffany had managed its brand. In February 2007, a hedge fund, Trian Fund Management LP, announced that it had bought a 5.5% stake in Tiffany, and became its largest shareholder. Trian believed that Tiffany was undervalued and stated that it wanted to help the company “improve its earnings per share by addressing various operational and strategic issues.” In response, Tiffany began to consider different actions to increase shareholder value.

TourAmerica is negotiating a master contract with Voyager Inn International (Bethesda) for hotel rooms during the 1995 tourist season. Issues under consideration include number of rooms during peak, mid-, and off-periods, room rates, breakfast prices, and the cost of ancillary services. While the hotel manager is evaluated on the basis of several criteria, including adjusted daily rates, occupancy rates, and food and beverage profitability, and is also provided with a utility scheme to facilitate trade-offs among the criteria, TourAmerica uses an effective cost per registrant (adjusted for intangibles). These two approaches provide an opportunity to contrast measurement schemes and to justify the use of utility functions. This case is a role-play exercise and must be used in conjunction with “Voyager Inn International” (UVA-QA-0463).

This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM).

The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]).

The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.

This case present the dilemma of an employee who, having been terminated in a manner he deems is unfair, has to decide whether to cash or return a $2,500 check wrongfully sent him by his former employer.

The owner/editor of the small Davis Press encounters a dilemma when she is given the opportunity to publish a novel set in the Islamic holy city of Mecca. Given the events of the last 16 years—the angry fallout after Salman Rushdie's novel The Satanic Verses, the continuing Iraq War, and the recent controversy of Koran desecration at the U.S. Naval Station Guantanamo Bay—publishing the novel presents a host of various ethical dilemmas, including whether she should put her staff at risk. This case discusses the ethics of a free press and challenges the profit motive in the face of jeopardizing political and religious world affairs.

This case concerns the troubles that Euro Disney experienced from the start. Euro Disney claimed that the major cause of its poor financial performance was the European recession and the strong French franc. The timing of the park's opening could not have been more inopportune. If the recession had been the only cause of Euro Disney's problems, the financial restructuring would only need to carry the park forward to better economic times. Only when Europeans began spending freely again would investors learn the answers to some uncomfortable questions: Was the whole idea of Euro Disney misconceived? Were there other fundamental cultural problems that could inhibit the park's success? Would Euro Disney fail to recover even though other European companies did? And, if so, why was the Disney theme-park concept successful in Japan and not in France?

Richard Alpert, senior partner at Evergreen Investments, must decide which of his two best employees to promote to the position of managing VP. He had initially preferred Charlie Pace over Daniel Faraday, but that decision had become less clear-cut when Alpert inadvertently overheard an office conversation and learned that Pace was taking Adderall, a stimulant primarily prescribed for people suffering from attention deficit/hyperactivity disorder (ADHD). Pace did not have ADHD and apparently obtained the medication by deceiving a physician. Alpert is faced with a number of questions, including whether it was fair to Faraday—or any other high-performing employee—to be passed over for promotion in favor of someone who illicitly boosted his performance with a substance he did not medically need.