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Two recently graduated MBA students are tasked with developing an ad-serving learning algorithm for a mobile ad-serving company. The case illustrates the way in which hypotheses can be tested in an A/B format or “horse race” in order to establish customer preferences and superior profitability. The case was written for a course elective covering hypothesis testing.

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 2006, four successful entrepreneurs decided to establish a world-class mega university. Initially, the project progressed slowly until Vineet Gupta was able to locate a small plot of land in Sonipat, Haryana. Forty-eight hours before the payment deadline, Ashish Dhawan and Sanjeev Bikchandani agreed to invest in their personal capital to kick start the project. They however suggested a pivot in favour of a smaller private liberal arts college. Meanwhile, Pramath Sinha, with prior experience in establishing the Indian School of Business launched a pilot through the Young India Fellowship (YIF). Dhawan and Bikchandani, through their extensive entrepreneurial networks, raised scholarships for the first two batches of the fellowship in the hope of attracting other donors to the board and getting a buy-in for Ashoka University. The team faced a number of challenges: managing the new model of collective philanthropy, recruiting faculty and finding jobs for the first undergraduate batch. At Ashoka University's first graduation ceremony in 2017 they wondered whether this model could revolutionise the higher education space like the IITs and IIMs had done for the country.

The decision maker is in charge of procurement auctions at the department of transportation of Orangia (a fictitious U.S. state). Students are asked to assist him in estimating the winning bids in various auctions concerning highway repair jobs using data on past auctions. The decision maker is faced with various professional, statistical, and ethical dilemmas.

To analyze highway procurement auctions from the buyer-auctioneer perspective, establish basic facts regarding the project price-to-estimated cost ratio, set up and estimate a structural regression model to predict the winning bid, and compute the probability the winning price will be below estimated cost. Difficulties include heteroskedasticity, logarithmic specification, and omitted variable bias. Also to estimate a Logit regression and predict bidder collusion probability.

Supplements the (A) case.

The case fosters discussions on basic concepts of entrepreneurship that include building a minimum viable product before launching a finished product, the importance of doing market research for early-stage startups, challenges in understanding an unfamiliar domain or industry and understanding the dynamics of business to business market.

Team Arnetta’s founders were interviewed in relation to the case. After the initial round of interviews, a product demonstration was given by Arnetta. Follow up interviews were conducted to delve-deeper into the problem while secondary research was conducted to understand the market dynamics and competitive landscape at the point in time in the case.

The four founders of Arnetta Technologies debate go-to-market timing for Integrated Breeding and Research Management Software, a data handling software for the R&D process followed by seed enterprises in India. The founders had spent over US$75,000 on the product development on which they had been working for more than one year. Two of the founders had given up their full-time jobs to work dedicatedly on the venture. The product was being customized to the requirements of their only client. Product development was taking longer than anticipated. To add to the challenges, international competitors had started capturing the Indian market. The founders had two options. First, they could wait and finish the product development before reaching out to their prospective clients – leading to delays and losing out on the market. Second, they could reach out to prospective clients and convince them to use the work-in-progress version of the product – which could turn out to be a deal breaker. The founders had to come to a consensus soon.

The case is intended for students in undergraduate or graduate-level courses related to entrepreneurship, new venture creation, innovation management and business management.

The learning outcomes of this paper are as follows: to understand the context of seaport logistics and supply chain design structure, to apply Monte Carlo simulation in the interface of the supply chain and to analyze the Monte Carlo simulation algorithm and statistical techniques for identifying the key seaport logistics factors.

It was 9:00 p.m. on November 10, 2020, and Nishadh Amonkar, the CEO of OCTO supply chain management (SCM) was glued to the television watching the final cricket match of the Indian Premier League, 2020. Amonkar’s mobile phone rang and it was a call from Vinod Nair, a member Logistics Panel of Ranji Industries Federation. Nair informed Amonkar that it was related to the rejection of several export consignments of agricultural products from Ranji (in the western part of India). The rejection was due to the deterioration in the quality of the exported agricultural products during transit from Ranji to various locations in Europe.

This course is suitable at the MBA level for the following courses: Operations research (Focus/Session: Applications on Monte Carlo Simulation). SCM (Focus/Session: Global SCM, Logistics Planning, Distribution Network). Logistics management (Focus/Session: Transportation Planning). Business statistics (Focus/Session: Application of Hypothesis Testing).

Teaching Notes are available for educators only.

CSS 9: Operations and logistics.

This case aims to study the growth, evolution, and social innovation of iThrive Games, a socially minded initiative that aims to create meaningful opportunities using technology for teens to enhance the knowledge, mindsets, and skills they need to thrive through development and across the continuum of mental disorder to wellness. iThrive's focus has been on creating “meaningful games”—that is, games that promote health and well-being of teen players. Founded in 2014 by Dorothy Batten, President of DN Batten Foundation, the organization's mission was to collaborate with game developers, partner with teens across the game development cycle (ideation to testing), and provide resources to foster teen thriving through gameplay. To do so, the organization took a unique social entrepreneurial approach. Drawing on a positive psychology framework and building the brand among key stakeholders including game developers, researchers, funders, youth, educators, and parents, the organization orchestrated a community dedicated to advancing the meaningful games field, and in doing so, have widespread impact.

Academic research cases (ARC) provide interesting learning situations and challenging problems to study. However, it can be difficult to bring these research cases to classroom teaching because the “answers” are embedded within the case studies. Research cases can be redesigned as teaching cases (TCs) through a method of unwrapping the ARC and re—visioning it as a TC. One method is provided in this paper.

The authors have taken an unpublished research study and rewritten it as a TC. Elements from both manuscripts are provided in tabular form to guide the creation of TCs by academic researchers.

This paper will be helpful for any academic who wishes to transform a qualitative research case study into a useful classroom teaching tool.