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This study aims to investigate the factors that contribute to the overall tour experience and services provided by Top Tier Holidays. The study is mixed in nature, and the researchers have used analytical tools to analyse the data factually. Multiple regression using MS Excel is used in the study.

This case is based on the experiences of a real-life travel and tour company located in New Delhi, India. The case helps understand regression analysis to identify independent variables significantly impacting the tour experience. The CEO of the company is focused on improving the overall customer experience. The CEO has identified six principal determinants (variables) applicable to tour companies’ success. These variables are hotel experience, transportation, cab driver, on-tour support, itinerary planning and pricing.

Multiple regression analysis using Microsoft Excel is conducted on the above determinants (the independent variables) and the overall tour experience (the dependent variable). This analysis would help identify the relationship between the independent and dependent variables and find the variables that significantly impact the dependent variable. This case also helps us appreciate the importance of various parameters that affect the overall customer tour experience and the challenges a tour operator company faces in the current competitive business environment.

This case is designed for discussion with the undergraduate courses in business management, commerce and tourism management programmes. The case will build up readers’ understanding of linear regression with multiple variables. It shows how multiple linear regression can help companies identify the significant variables affecting business outcomes.

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.

Alice Monroe was an admissions officer at the Kellogg School of Management at Northwestern University. It was early January 2017 and Alice had enrolled in Northwestern's 403(b) retirement plan two months earlier. After spending a considerable amount of time examining the mutual funds available through the university's retirement plan, Alice had picked two to invest in: a large-cap equity growth fund and a mid-cap equity fund. (See the related case "Selecting Mutual Funds for Retirement Accounts (A).") Her initial allocations were 50% of her investment dollars in each fund.

Upon further reflection, however, she realized these initial allocations were somewhat simplistic. She recalled, from an investments class she had taken at college, the topic of modern portfolio theory, which held that by adding more funds to her portfolio she might be able to achieve greater diversification and thereby reduce the overall risk of her portfolio and/or achieve a higher expected return. Alice now was considering adding an intermediate-term bond fund and a real estate fund to her retirement account.

She hoped to use modern portfolio theory to prove that these new funds would indeed help her diversify her portfolio. If they did, she would also reassess her portfolio weights to determine the optimal allocation.

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.

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.

The case primarily focused on a real-life problem and shows that existing operations management tools can be used to solve a complex problem. Through this case, the participants will learn the application of the factor loading method and aggregate planning.

This case revolves around the Modi Agro Pvt. Ltd, a mango procurement and distribution business established in 1994 by Mr Dhanush Modi in Mumbai, India. Mr Mahendra Modi, son of the company owner, observed that the different seasons of cultivation and varied customer demands lead to changing workforce requirements during the procurement process. In addition, the production quality, variety, available resources, procurement location and cost play a significant role in establishing a long-term relationship with the customers. This case highlights the problem faced by Mahendra in determining an appropriate location among all available options for mango procurement and the optimal workforce for each month to meet the varying customers’ demands.

The case can be used as teaching material for participants of the course Service Operations Management, Operations Management, Decision Analysis and Quantitative Techniques

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

Alice Monroe, a 30-year-old married mother of two, was an admissions officer at the Kellogg School of Management at Northwestern University. She was just completing her first year of service at Northwestern and qualified for the university's 403(b) retirement plan. It was early October 2017, and she had until the end of the month to decide if and to what extent she would participate in Northwestern's retirement plan–that is, how much of her salary should she put into the retirement plan, and into which mutual fund or funds should she allocate her savings?

The case includes background on defined contribution and benefit plans as well as mutual funds. It goes into detail about Northwestern's retirement plan, including data on the performance of 15 of the plan's core mutual funds. The case also provides each fund's strategy, Morningstar Rating and Morningstar Category, expense ratio, assets under management, turnover rate, and historical performance for the last 10 years.

Using modern portfolio theory (diversification and risk-return trade-off) and with an understanding of mutual fund fees and the tax advantages of retirement savings, students will decide how much Alice should invest and in which mutual funds.

Marketing, retail.

The case study is specific to the marketing demographics of Indian shoppers with respect to organized retail stores, and therefore, the inter-relationships between various design elements and the relative importance of certain parameters discussed in the text may not follow the same pattern elsewhere in the world.

The case emulates the real-life situation of an organized retail store, Super Mart, to understand the inculcation of voice of the customer in the design of organized retail stores in India. It gives insights about factors which influence the shopping intent of customers while giving information about the inter-relationships among various design characteristics. It also gives an idea about inter-dependence between design characteristics and customer requirements. This is followed by certain questions, the responses to which can be interpreted from the text and the data provided therein.

The case aims to educate its audience about the following aspects of organized retail business: factors influencing offline shopping intent of customers; relative order of importance of customer requirements with respect to organized retail stores; inter-relationships between various design elements; and future trends in the organized retail space. Such a knowledge would help hone the skills of the next generation of business leaders in the retail space.

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

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.

Josh Williams is a Student at the NAU who has driven buses on campus and wants to improve the transportation on campus. He is convinced that purchasing a new type of bus that is more fuel efficient, has larger capacity, better designed for boarding, and has a longer life is worth the higher purchase cost. He sets out to prove it by creating a discounted cash flow (DCF) analysis. Since many of the estimates for the DCF analysis are uncertain, he decides to perform a Monte Carlo simulation (MCS) analysis. Students are asked to step into Josh’s role and perform the analysis.

Josh Williams was a Student in the authors’ MBA program. Both authors teach in this program and one author was the Advisor for Net Impact and worked with Josh to present his idea to the university administration. The authors have changed a name or two but otherwise, the case describes a real situation in a real organization without disguise.

The authors have used this case in a first semester MBA-Applied Management course, Decision Modeling and Simulation. Students already have experience with DCF analysis and have been introduced to MCS. With this case, students apply MCS at the conclusion of a three-week module on predictive analytics. Students have run at least two MCS models and have become comfortable with the software. The case would also be appropriate for a senior-level undergraduate course such as business analytics or management science. It might also be useful for other courses that include the MCS modeling technique learning objectives such as project management.

This case provides an opportunity for students to perform an MCS analysis. MCS is useful when many of the inputs to a DCF analysis (or any model) have been estimated and the modeler is concerned that the estimates are uncertain and could perhaps be a range of values. MCS can be used to understand the effect of this uncertainty on NPV which in turn may affect the decision. The case could also be used without MCS focusing just on the DCF analysis with deterministic sensitivity analysis.