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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.

The case describes the policies followed by the Government of India to attract private investments for Oil & Gas exploration. This case is based around observations made by the Comptroller and Auditor General of India on some of the petroleum sharing contracts and the remedial measures suggested by a committee appointed by the Government. The case describes how such contracts are structured elsewhere and raises issue about how such contracts can be structured and managed by the state.

This case features a prominent antidumping case in the United States against six of its major foreign shrimp suppliers. The case fits well in a discussion and analysis of the (welfare) consequences of protectionism, the basic case for free trade, and the political economy of protectionism.

EuroPet S.A. was a multinational company operating gas stations in many European countries. There was a growing propensity for supermarkets to attach gas stations to their retail operations, which was developing into a major threat to EuroPet. As a result, in the mid-1990s, the company began to develop and brand its own convenience stores co-located with its gas stations. However, the company was spending much more on advertising the convenience stores than its competitors did. Management now had to decide if the increase in sales attributed to advertising efforts justified the advertising spend by analyzing the market data from one large metropolitan area: Marseille, France.

Students will learn: how to use cross-tabs and other marketing research tools to identify segmentation descriptors; how to analyze data and interpret results; and how these research results could guide new product development and positioning strategies in order to effectively target relevant customer segments.

This two-part case illustrates the use of economic order quantity to manage conflicting performance measures across different siloed functions in an organization. Part A requires students to assess the costs of various order quantities and quantify the concept of “robustness.“ Part B emphasizes managing the variables of annual demand, ordering cost, inventory carrying cost, and unit price to achieve strategic goals. The student must determine how to lower ordering costs to compensate for increases in the other variables as well as to help guide Just-In-Time implementation efforts.

This case is the second of a three-part series that follows the managerial, strategic, and communications decisions of the Swachh Bharat Mission (SBM) or Clean India Mission, the flagship programme of the Government of India to eliminate the practice of open defecation (i.e., not using a toilet) from 2014 to 2019. As of 2014, 550 million people in India practiced open defecation. This problem posed a massive public health hazard and economic drag for the country as well as a threat to global health. Written from an insider's perspective, the cases centre on the decisions made by a new Secretary of India's Ministry of Drinking Water and Sanitation, who was hired to manage SBM, and the team he assembled. Case B discusses the start-up challenges for SBM, including implementation in India's complex federal system, workplace culture, and the deep-rooted behaviour of open defecation in rural India and the managerial and communication strategies formulated to address them. The case concludes by framing the difficulties with slow-moving states and monitoring rigour that the leadership SBM, with a new team, strategic focus, and early momentum, faced as the mission entered its final two years.

This case is the first of a three-part series that follows the managerial, strategic, and communications decisions of the Swachh Bharat Mission (SBM) or Clean India Mission, the flagship programme of the Government of India to eliminate the practice of open defecation (i.e., not using a toilet) from 2014 to 2019. As of 2014, 550 million people in India practiced open defecation. This problem posed a massive public health hazard and economic drag for the country as well as a threat to global health. Written from an insider's perspective, the cases centre on the decisions made by a new Secretary of the India's Ministry of Drinking Water and Sanitation, who was hired to manage SBM, and the team he assembled. Case A sets the stage for addressing open defecation in rural India and discusses the human resources and strategic challenges to implementing SBM from the vantage point of the new Secretary. It ends with strategic dilemmas related to what the new SBM team should do once they had sized up the challenges to eliminating open defecation by 2019. The case provides an opportunity to deliberate the managerial and strategic decisions of a globally relevant public behaviour change and rural infrastructure development program as well as different forms of public sector implementation in the Indian context.