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Nicolas Dupont, the owner of Chateau de Montana, a struggling (and old) boutique hotel in Crans-Montana Ski Resort, Switzerland, wished to renovate and reposition his family-owned hotel to target higher room rates. Dupont commissioned Olga Mitireva and Yulia Belopilskaya as consultants to assess the proposition. The consultants had to extract cues for the room rate of the repositioned hotel from comparable hotels. However, the room rates varied significantly across similar hotels due to their differing characteristics and locations. It was a cognitive challenge to read the patterns from a few comparable hotels. They collected the data of 200 hotels from similar locations and simulated room prices using hedonic regression models.

The case has the following learning objectives:

1. understand the various types of comparisons that are possible between groups over time and across space;

2. evaluate a policy intervention using relevant data and different methods; and

3. understand the meaning of the phrase “controlling for other relevant factors” in regression and non-regression contexts.

The difference-in-differences (DID) approach is a useful tool for making meaningful comparisons. This case tries to provide a non-technical introduction to the approach using a basic comparison of crime rates among districts in Punjab (Pakistan's largest province). Being the most populous region of the country, Punjab faces many governance challenges, and street crime is one of them. (Exhibit 5 provides additional information about the geographical and administrative setting used in this case study.) In 2016, Chief Minister Shahbaz Sharif established the Dolphin (police) Force in different locations to improve urban patrolling and reduce street crime. There were debates about the effectiveness of the Dolphin Force (DF).

Those who are skeptical of DF point to various situations that were handled incorrectly by DF personnel, as well as other administrative and operational problems in the initiative. Optimists believe it is beneficial and want it to be expanded to other districts and regions. The threat of street crime claims many lives and, according to optimists, necessitates the formation of a special force. Whether the huge resources invested in the DF worth their lot or not can be known through sound statistical analysis that can identify the difference in the rate of crime because of the DF. In this instance, the case provides information to answer the following question:

Is there a significant difference in crime rates between areas where the DF is operating and districts where it has not yet been installed?

In quantitative/statistical analysis classes, the case can be used to teach the DID technique to MBA/MS Applied Statistics/Applied Data Analysis students. It can also be used in undergraduate Econometrics classes.

Teaching notes are available for educators only.

CSS 7: Management Science.

During one of the most nerve-wracking football matches of the 2012–2013 Bundesliga season, life-long friends Franz Dully and Max Vogel begin arguing about whether the wealth of a football club determines its success during the season. In order to disprove Vogel's claim that “money scores goals,” Dully must analyze the Bundesliga's current market values, points earned, and mid-season leader data.

After analyzing the case, students will be able to compute prediction intervals, develop regression models, and interpret data. The development of the regression models asks students to choose the relevant set of independent variables, as well as determine an appropriate functional form for the regression equation. The models derived have to be evaluated as well as compared to one another. Further, the students have to interpret the quantitative findings in the context of the application.

Illinois Superconductor Corp. a technology start-up, came up with an innovative new superconducting filter for use in cellular base stations. It needed to estimate the demand for its filters. The manager came up with a simple chain-ratio-based forecasting model that, while simple and intuitive, was too simplistic. The company had also commissioned a research firm to develop a model-based forecast. The model-based forecast used diffusion modeling, analogy-based forecasting, and conjoint analysis to create a forecast that incorporated customer preferences, diffusion effects, and competitive dynamics.

To use the data to generate a model-based forecast and to reconcile the model-based forecast with the manager's forecast. Requires sophisticated spreadsheet modeling and the application of advanced forecasting techniques.

Wall Street hedge fund manager Kim Meyer is considering investing in an SFA (slate financing arrangement) in Hollywood. Dave Griffith, a Hollywood producer, is pitching for the investment and has conducted a broad analysis of recent movie data to determine the important drivers of a movie’s success. In order to convince Meyer to invest in an SFA, Griffith must anticipate possible questions to maximize his persuasiveness.

Students will analyze the factors driving a movie’s revenue using various statistical methods, including calculating point estimates, computing confidence intervals, conducting hypothesis tests, and developing regression models (in which they must both choose the relevant set of independent variables as well as determine an appropriate functional form for the regression equation). The case also requires the interpretation of the quantitative findings in the context of the application.

In April 1992, this multinational consumer foods and beverages company is the focus of takeover rumors, which have prompted an assessment of the firm's returns. The student must choose among the principal methods of estimating the weighted-average cost of capital (WACC) for GrandMet and its three main business segments, and must then produce WACC estimates in order to evaluate the firm's performance.

This case study intends to add knowledge and understanding of supply chain management particularly with respect to international logistics.

The case study can be used in both undergraduate and postgraduate levels. Students pursuing Master of Science in Logistics, Supply Chain Management and those doing bachelor degrees in the same areas can have a better insight and special interest of the case. Professional boards may also use the case to empirically make students understand this area.

The railway sub-sector in East Africa – Tanzania in particular – is an important transport mode but has a declining performance. The market share is estimated at only 4 percent of the freight market. Still knowledge about traffic, particularly for freight, is scant. The main dilemma is whether traffic of the central corridor is more intra- or inter-Tanzania. The case studies techniques appropriate for meaningful traffic forecasting and through a simple regression model it resolves the freight conflicts between Kenya rail and the Central Corridor. It provides students with applied traffic forecasting tools.

The case focuses on techniques of traffic forecasting, development of traffic scenarios and on issues related to intermodal transport especially between road, rail and ocean. At the end of using this Case students should be able to: explain the methods, techniques and models used in traffic forecasting; understand intermodal linkages in international Logistics; use different approaches to make logistics market assessment; and forecast traffic in all modes using different scenarios.

Teaching notes are available for educators only. Please contact your library to gain login details or e-mail support@emeraldinsight.com to request teaching notes.

This case consists of conversations with six prominent venture capital investors in the United States. The topics covered include investment strategies and relationships with entrepreneurs in the United States and around the world.

Jennifer McDougall is considering investing in mutual funds for the first time, and has narrowed her options down to three: one that is domiciled in Germany, and two that are domiciled in Luxembourg. As a cautious and risk-averse investor, Jennifer has done extensive research on the three funds, and has come across a curious fact: the beta of the German fund is surprisingly low. After speaking to her financial planner, she learns there is no legal requirement in Germany for mutual funds to compute net asset values at a particular time of the day. If the German fund is closing its books in the middle of the day and its net asset values reflect its midday holdings, rather than end-of-day holdings, this could explain the low beta. Thus, the German fund might appear less risky, without actually being so. Jennifer needed to get a clearer picture of what was going on before making her decision.

Using the data provided with the case, students will determine the closing time of the three funds and how that affects the beta of each. Then they must make a recommendation about which fund would be the best investment for Jennifer.

Dick Mayo, one of the most celebrated value investors in America was puzzled by the New Economy's continuous bias toward growth investment strategies. He examines the basics of his philosophy versus that of a growth orientation by evaluating the long-term expected returns of several value and growth stocks. This case can be used to pursue several objectives: (1) to define value and growth investing-where the differences lie and whether one approach is superior to the other or whether both have merit; and (2) to discuss issues related to consistency of one's investment philosophy. Should one stay true to one's philosophy even when the market seems to run counter to it for a prolonged period of time? Can value investing deliver value in this New Economy or is it only an Old Economy concept? The students are instructed to perform basic valuations of Cisco Systems (a growth company), CVS, R.R. Donnelley, and Manor Care (value companies) and compute their long-term expected returns. The case comes with an Excel spreadsheet containing the data and relevant valuation ratios for the above firms. The valuations are straightforward, but they tell an interesting story: the expected returns of glamorous stocks in reality may not be so glamorous.