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The case deals with marketing research study undertaken to introduce a new product in the market. The company was planning to introduce Cerenity, a toilet seat sanitizer for women who frequently use shared restrooms. The case discusses the conclusive study undertaken involving quantitative marketing research. The research team carried out quantitative survey and collected the data. It applied various quantitative research methods such as factor analysis, multiple regression, cluster analysis and conjoint analysis for analysis the collected and drawing managerial inferences.

Data used to develop the case included primary data from employees and supervisors of a commercial floorcovering manufacturing plant in Northwest Georgia. The case company is not disguised.

The survey was developed using existing instruments from the Organizational Behavior and Human Resources Literature. Instruments were listed in Exhibits 2 through 7. The survey administration had the support of the Vice President for Resources and Facilities, and employees and their supervisors were given time to complete the surveys. The data gathered was analyzed by the researcher using SPSS statistical software.

Established in 1957, J&J started as a family-owned business but had grown and diversified its product offerings by focusing on commercial flooring. It survived several economic downturns and remained competitive in a market dominated by more prominent flooring manufacturers. J&J Industries strived to empower its 800 employees with various incentive programs. Employees remained loyal to J&J; many had worked for the company for over 15 years. However, management wanted to measure the impact of empowering and initiatives on employee performance and satisfaction to determine the real power of employee incentive programs. The Resources and Facilities Vice President employed Professor Lopez, a Management Professor, to develop a survey to measure these constructs and analyze the data to guide future incentive programs. Data from the employee and supervisor survey was provided along with the statistical analysis results for interpretation and recommendations for VP Fordham.

The target audience for this case is primarily students in a research methodology course and students studying quantitative regression analysis and interpretation. The focus is predominantly on graduate-level students in Master of Business Administration or Master of Accounting programs in business. Graduate students should have completed courses in management or organizational behavior, business statistics or quantitative methods or data visualization and cleaning as background knowledge for this case. Specifically, students should understand regression analysis and know when and how the tool is used for managerial decision-making.

Faeyee Electronics was an electronics company that manufactured and sold smartphones including XS and XT types. The management of Faeyee wanted to pursue the maximum contribution margin as much as possible, especially since they were faced with limited resources. It was necessary to apply analytical tools and cost accounting concepts to study this case including cost-volume-profit analysis, learning curve analysis, regression analysis, definitions of competitive products, constrained non-linear optimization, and contribution margin.

The case uses business analytics tools and cost accounting concepts, including regression models and constrained optimization approaches, to study how to maximize business outcomes, such as contribution margin and profits when limited business resources are available. The company and individuals are disguised.

This case can be used in any junior-, senior-, masters- or MBA-level managerial accounting course. Students need to have at least one course of introduction to statistics or instructors review required statistics concepts or techniques before assigning this case. Students are exposed to the challenges of deriving learning curve models, using regression analysis to study collected data and allocating limited resources to maximize contribution margin.

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.

Spiegel Online (www.spiegel.de) is the leading news Web site in Germany. The site was first designed to accompany Der Spiegel, one of Europe's largest and Germany's most influential weekly magazine, which has a weekly circulation of around one million. The site's content is produced by a team of more than fifty journalists writing in several categories: politics, business, networld, panorama, arts and entertainment, science, university, school, sports, travel, weather, and automobiles. The original content is complemented by articles purchased from news agencies and selected articles from the print edition. Spiegel-Verlag is a major contributor to the Hamburg Media School, which offers professional master's degree programs in Media Management (MBA), film, and journalism. In their second year, MBA students typically engage in consulting projects with major media companies. In a recent assignment, Spiegel Online posed two questions to the MBA team: are there any chances for an economically successful entry into the market for interactive classifieds? And if so, what should the business model look like in detail? A student team analyzed markets for classified ads and found one market segment that appeared to be particularly promising: the market for art objects. During the development of a business plan for a new venture in this market it became apparent that there is much uncertainty about the key input parameters to the business plan. As a result, it is very difficult to assess the viability of the business idea. How can the team properly account for the uncertain input parameters? What is the impact of this uncertainty on the bottom line? Will a Web site for art objects earn or lose money? How can the team communicate this uncertainty to a group of high-level decision makers who want a simple “go or no-go” recommendation?

The objective is to make students aware of the applicability of Monte Carlo simulation to the analysis of complex business plans. Students should learn how to explicitly account for uncertain inputs in a business plan, how to assess the impact of uncertainty on the bottom line via Monte Carlo simulation, and how to communicate the results of their analysis to high-level decision makers.

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.

This study aims to use a variant from the family of discrete choice models, i.e. the logit model, to analyse the relationship between the Y dependent and X explanatory variables. This model addresses the linear probability model's main drawback by constraining the probabilities of the Y outcome between 0 and 1. The logit model also offers an extra advantage, in that it can provide odd ratio estimations.

This is a compact case written specifically to teach statistics, econometrics and research method. It has an accompanying data set for the case-users to do hands-on statistical analyses. The data set has been collected from a questionnaire survey from the students enrolled in Attitune, i.e. the music school that the case protagonist founded.

The case revolves around a relatively new music school, Attitune Music, established in July 2017 in the heart of the capital city of a northern state in Malaysia. Michael Lee Wei-Pin was the founder of Attitune Music Sdn. Bhd. He was also one of the four music instructors of Attitune Music. His speciality instruments were the guitar and the piano. The case opens with the case protagonist, Michael, pondering over Attitune’s performance in terms of its music students’ enrolment. Attitune faced a major challenge – its student enrolment had remained more or less constant since its establishment. Low and/or constant number of students could ultimately translate into stagnant or even worse, shrinking revenues for Attitune. To attract more students, Michael had been toying with the idea of injecting new elements into Attitune’s music lessons, something different from what other music schools were offering and that could be unique selling points for Attitune. With this in mind, Michael surveyed Attitune’s students to gather information that could help him gauge the potential and feasibility of his idea.

This case is well positioned to be perhaps the pioneer Malaysian teaching case to be written to teach courses in statistics, econometrics and research methods. The case can be easily adapted to teach at either the introductory or at an advanced level.

In 2013, ‘Fashion Destination’, a well-established clothing retailer considered setting up a clothing and accessories rental service. They hired a market research agency ‘Wright & Company’ to conduct a research on the sustainability and profitability of such a business model. The consultants collected primary data and did an extensive analysis for Fashion Destination. Based on the secondary research, expert interviews, extensive qualitative and quantitative research the consultants recommended the management to start a clothes and accessories rental service but suggested that the product offering be limited to formal clothes only and offer accessories. Vishal had doubts despite of the go-ahead signal from consultancy. He wondered what recommendations should he accept and which needed further verification.

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.

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.