Search results

With the development of inclusive financial business in China in recent years, this case describes the credit risk control of “mobile credit”, a smart online credit platform launched by Shanghai Mobanker Co. Ltd. (referred to as “Mobanker”, previously named as “Shanghai Mobanker Financial Information Service Co., Ltd.”) which provides technical services for inclusive finance industry.

The case evolves around the Powerball lottery and the rule changes implemented in 2015, which, among other things, changed the chances of winning the jackpot from 1 in 175 million to 1 in 292 million. What is the impact of such rules on lottery revenues? The expected value rule is unable to explain why people play in the first place and fails to give the appropriate weight to the factors that explain the attractiveness of a lottery. This case is ideal to introduce the notion of decision weights as put forward by Kahneman and Tversky's prospect theory. By calculating decision weights, we obtain a reasonable prediction for the willingness to pay for the lottery as a function of different jackpot amounts. Using past data, we can correlate lottery revenues with predicted willingness to pay for a ticket. Quantitative-inclined audiences can then develop a simulation model of how likely it is that the jackpot grows, which, coupled with the prediction of revenues as a function of the jackpot, would give the evolution of the revenues under the new rule. The accompanying spreadsheet provides data for students to work out various scenarios to narrow objectives and maximize revenue from Powerball tickets.

The financial success of dairy farms depends critically on the price of their main output, milk. Large volatility in the price of milk poses a considerable business risk to dairy farms. This is particularly true for family-run dairy farms. The question then arises: how can a farm owner hedge the milk price risk? The standard approach to establish a price floor for a commodity such as milk is to purchase put options on commodity futures. At the Chicago Mercantile Exchange, farmers can buy put options on the price of a variety of milk products. However, the price a farm receives for its milk depends on many factors and is unique to the farm. Thus, a farmer cannot directly buy put options on the price he receives for the milk his farm produces. Instead the farmer needs to determine which of the options available for trade at the Chicago Mercantile Exchange offer the best hedge for his own milk price. The assignment in this case is to examine historical data on several prices of milk products and the milk price received by a family-run dairy farm in California. Students need to find the price that is most closely correlated to the farm's milk price and to then choose options with the appropriate strike price that serve as the best hedge for the farm's price risk.

The objective is to expose students to an interesting but simple finance application of linear regression analysis. To solve the case, students must run several simple linear regressions, then use the best regression model they find to make a prediction for the dependent price variable and analyze the prediction interval in order to achieve the desired objective outlined in the case. By completing the case, students will acquire a good understanding of their regression model and its usefulness.

The first three years of operation of the West Kendall Baptist Hospital (WKBH) in Miami, Florida provided a “poster child” for efficient and cost effective healthcare delivery to the West Kendall community that it served. The hospital leadership and management team exemplified a quality-oriented staff that moved as a cohesive and dedicated organization. WKBH exceeded every budget prediction and showed a profit in year 3, well before expected. Then came the winds of regulatory change. With the passage of the Affordable Care Act (ACA) and the attendant imposition of new reimbursement metrics, the picture at WKBH changed almost overnight. By the first quarter of 2016, WKBH started to lose money in excess of budget predictions despite its increased patient admissions, careful financial planning, expense reductions, quality service, and excellence in patient care delivery. A serious financial crisis was looming with little relief in sight. The hospital management team began to search for solutions.

The research methodology includes collecting quantitative data: original financial statements and financial data from WKBH, as well as qualitative data: interviews of hospital administrators and historical information.

Graduate capstone course in a finance course; masters in health administration; and/or the MBA program.

While it is clear that the ACA was designed with all good intentions, it has created substantial and perhaps, unanticipated financial burdens for caregivers. These issues are not only faced by WKBH. Most hospitals could relate to one or more of the four questions examined as part of this learning process. Graduate MBA students worked with the hospital to identify, define, focus, and resolve difficult quantitative and qualitative issues faced by the hospital as a result of major changes in the regulatory environment with the passage of the ACA. This case focuses upon the current reimbursement environment that has only recently emerged as a result of the implementation of the ACA.

Corporate entrepreneurship; Intrapreneurship; Human Resources.

MBA students in Human Resource, entrepreneurship and/or PhD students in the areas of Human Resource, Corporate Entrepreneurship and/or on Intrapreneurship studies.

This case reveals that progressive change originated from individual’s positive deviance approaches, opportunistic sensitivity, ability to learn, evaluate and the ability to develop ideas on how to exploit or pursue identified opportunities (intrapreneurial behaviour).

The student will learn to deal with the complex nature of organisations and the tendencies of institutional processes to be uncertain, unpredictable, and uncontrollable; appreciate the internal workings of an organisation, the external environment; and understand the role of generative leadership, positive deviance, novelty ecosystems and intrapreneurial behaviour and the fact that connections and interactions in a social network are non-linear or non-proportional. This means that complex system predictions can be much more than simple regression predictions. They will be able to apply both bottom-up and top-down influences from proactive leadership or generative leadership events and benefit from positive results and the emergence of innovation.

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

CSS: 3 Entrepreneurship.

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.

Case can be taught at the undergraduate or postgraduate level, including executive Master of Business Administration programs.

This case is intended for courses in strategic management, entrepreneurship and innovation at the undergraduate or postgraduate level.

The case is about challenges faced by Linda Portnoff, the Co-founder and Chief Executive Officer of Riteband, a Sweden-based fintech startup. In March 2020, Portnoff was conducting beta testing of Riteband’s app, which experts considered the world’s first stock exchange for music trading. After completing a PhD, Portnoff who was working as a Research Analyst, left her job to pursue entrepreneurship. Through Riteband, Portnoff helped to resolve pain points of artists who were forced to give the copyright of their music tracks or albums to distributors, in lieu of funds or promotional campaigns that distributors arranged for them. Portnoff invested in developing a patent-pending machine learning-based algorithm that based on several parameters could predict the likelihood of a music track or an album to become a success. Based on this prediction and royalty that artists were interested in sharing with fans, shares were issued to investors, who were also fans of the artists. As Portnoff identified an innovative business opportunity to trade music on a stock exchange based on Riteband’s machine learning algorithm, competition in Riteband’s strategic group was also becoming intense. Consequently, Portnoff was facing challenges of establishing competitive advantage of Riteband. Furthermore, as women in general faced challenges in raising funds for their startups, and even though Portnoff obtained some funding for Riteband, but overall, funding was a challenge for her as well. Moreover, as machine learning was a technical aspect for artists and potential investors, Portnoff also faced challenges to monetize on its machine learning algorithm.

By the end of the case study discussion, students should be able to: understand the principles of cross-industry innovation and explain the creation of new business opportunities based on cross-industry innovation; differentiate between direct and indirect competitors through strategic group analysis and further critically analyze the competitive advantage of business over other direct competitors; determine ways of reducing gender biases in venture capital funding; describe how machine learning works and further formulate ways to monetize a business through machine learning; and demonstrate the application of the value proposition canvas and business model canvas.

CSS 3: Entrepreneurship; CSS 11: Strategy.

thyssenkrupp Steel Europe, a major European steel company, operates a so-called push-pickling line (PPL) in Bochum, Germany. The PPL produces a particular type of steel strips that are sold to B2B customers, mainly in the automotive industry. In spring 2014, a senior vice president of thyssenkrupp Steel's production operations and one of his production managers notice that over the span of ten years the production facility regularly did not meet its planned production volumes. They set out to determine the drivers for the deviations from planned production figures with the ultimate goal to improve the production planning process at the Bochum PPL. Students will step into the shoes of Markus Schulze a production manager at thyssenkrupp Steel as he searches for performance drivers at the Bochum PPL and analyzes recent production data to build a forecasting model for production planning.

Managerial Accounting, Strategic Marketing. More specifically, cost behavior, cost estimation, cost prediction, cost-volume-profit (CVP) analysis, contribution income statement and pricing/promotional strategy.

This case is suitable to be used in advanced undergraduate level.

This case demonstrates the issues relating to pricing strategy of “Video Internet Marketing Training”. Diyana Tahir and her husband, Abdul Rahim Abdul Shukor, established Aras Design & Multimedia Centre (ADMC) on January 17, 2009. The main office was located at Kuala Lumpur. Diyana was a well-known name in the field of internet video marketing training. In its early years, ADMC’s operation was limited to providing printing and graphic design services and offering printing materials for photocopy. However, with the passage of time, the company began to expand its services and offerings. At the beginning of 2010, ADMC offered editing facilities and services for video and multimedia in addition to its core services. As a unique marketing strategy, Diyana offered RM30 as the basic training fee for each participant, which was equivalent to RM470 value offered. In this way, she attracted customers to take part in further advanced level training that was conducted by ADMC. However, she felt that the number of participant to take advanced training was not satisfactory. She thought that it happened perhaps due to the fact that the participants were not much committed to the course since it was offered at a nominal price. Furthermore, she realized that the cost of providing such training had risen in the past six months. Currently, ADMC suffered losses in three consecutive months, and they really needed enough cash to sustain. As such, Diyana was thinking to reconsider the offered course fees whether to increase it. She was in a rush to make a decision to propose the new course fee in the monthly meeting with management committee at the end of April 2013.

Using this case, students can learn how a small-scale company can strategize its pricing strategy to survive in the highly competitive online market. The objectives of using this case are as follows: to help students in understanding the interrelationships between CVP in organization that can be used for future planning and decision-making; to be able to identify the cost structure of the basic training course (e.g. fixed and variable costs), determine the contribution margin, break-even point and prepare the contribution income statement that highlighting cost behavior; to help students to think critically while setting the price for the offered services; to develop students’ ability in analyzing the existing situation to come up with a viable and effective solution; to assist students in taking the right move in a right time; to broaden students’ views and understanding in considering the monetary aspect along with the human aspect in formulating an effective marketing strategy; to develop students’ understanding of the way to retain and attract customers through innovative pricing strategy; and to make students aware that innovation is the key to business success.

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

CSS 1: Accounting and Finance.

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.