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Align Inc. is a start-up company with a revolutionary, patent-protected new technology for straightening teeth called Invisalign. Invisalign is a set of invisible plastic aligners made to each patient's specific needs that substitute for metal or ceramic braces in adults (it is not sold for children's orthodontic needs). The company has created tremendous consumer awareness and affect for its product, yet sales results are dismal. Requires the reader to analyze the reasons for such poor sales and what to do to remedy the problem.

To examine distribution channel issues as well as the marketing mix for a new product introduction.

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.

The case is presented as descriptive in nature and primarily involves exploratory research.

Ashraf, a young graduate from Bangalore, India, started a chain of lifestyle shops, his family business in Khartoum, Sudan. To modernize the shops, Ashraf approached a small finance bank for financial assistance. However, after submitting the required documents and with a good credit score, he was denied a loan. The bank officials had mentioned that the loan automation software did not approve the application. Hence, the bank personnel said that they could not do anything further. Disappointed, Ashraf sought the help of his professor, John, to understand why the software rejected his application. Professor John explained to Ashraf the advantages and disadvantages of automation. In the process, Ashraf understood the significance and compelling need to address “Algorithm Bias,” a situation in which specific attributes of an algorithm cause unfair outcomes. The case place students in Ashraf’s position to help them understand the advantages and issues of applying automation through artificial intelligence.

The case suits graduate-level courses like business analytics, financial analytics and business intelligence.

Through the case, the students will be able to: Understand the role of algorithms in business and society. Understand the causes, effects and methods of reducing algorithm bias. Demonstrate the ability to detect algorithm bias. Define policies to mitigate algorithm bias.

The learning outcome is that it will help to sustain your startups in the ever-changing business environment especially in the context of emerging markets.

The present case is about Dilkhush Kumar from village Bangaon, India who developed a cab booking platform “AryaGo”, an innovative platform completely dedicated for rural road transport connectivity. AryaGo is the service line of Aryan Cabs and Rural Trans-solution Pvt. Ltd., a Startup founded in the year 2016 under Startup Bihar, a seed capital support scheme of State Government. The idea was to provide comfort, convenience, safety and affordability to all the commuters travelling from or within far-off villages. The biggest challenge during implementation in villages includes availability of updated geo-mapped images for app development and vehicle tracking. Company was foremost in providing the kiosk-based booking facility for its customers. It took the decision based on the profiling of customers and their preferred booking methods. When a customer booked a cab using IVR, they did not had access to app-based customer panel and hence they could not avail services such as, location tracking, SoS, real time tracking of vehicle. However, heavy invest in IT has put the company in financial stress and Kumar is wondering whether to expand fast or penetrate in the given target market. Should he re-design his business model so as it can really make a difference in terms of service delivery?

Post Graduate/ MBA.

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 8: Marketing

This case is designed to enable students to understand the role of women in artificial intelligence (AI); understand the importance of ethics and diversity in the AI field; discuss the ethical issues of AI; study the implications of unethical AI; examine the dark side of corporate-backed AI research and the difficult relationship between corporate interests and AI ethics research; understand the role played by Gebru in promoting diversity and ethics in AI; and explore how Gebru can attract more women researchers in AI and lead the movement toward inclusive and equitable technology.

The case discusses how Timnit Gebru (She), a prominent AI researcher and former co-lead of the Ethical AI research team at Google, is leading the way in promoting diversity, inclusion and ethics in AI. Gebru, one of the most high-profile black women researchers, is an influential voice in the emerging field of ethical AI, which identifies issues based on bias, fairness, and responsibility. Gebru was fired from Google in December 2020 after the company asked her to retract a research paper she had co-authored about the pitfalls of large language models and embedded racial and gender bias in AI. While Google maintained that Gebru had resigned, she said she had been fired from her job after she had raised issues of discrimination in the workplace and drawn attention to bias in AI. In early December 2021, a year after being ousted from Google, Gebru launched an independent community-driven AI research organization called Distributed Artificial Intelligence Research (DAIR) to develop ethical AI, counter the influence of Big Tech in research and development of AI and increase the presence and inclusion of black researchers in the field of AI. The case discusses Gebru’s journey in creating DAIR, the goals of the organization and some of the challenges she could face along the way. As Gebru seeks to increase diversity in the field of AI and reduce the negative impacts of bias in the training data used in AI models, the challenges before her would be to develop a sustainable revenue model for DAIR, influence AI policies and practices inside Big Tech companies from the outside, inspire and encourage more women to enter the AI field and build a decentralized base of AI expertise.

This case is meant for MBA students.

Teaching Notes are available for educators only.

CCS 11: Strategy

Rob Griffin, senior vice president and U.S. director of search for Media Contacts, a communications consulting firm, is faced with the task of optimizing search engine marketing (SEM) for Air France. At the time of the case, SEM had become an advertising phenomenon, with North American advertisers spending $9.4 billion in the SEM channel, up 62% from 2005. Moving forward, Griffin wants to ensure that the team keeps its leading edge and delivers the results Air France requires for optimal Internet sales growth. The case centers upon Air France's and Media Contacts' efforts to find the ideal SEM campaign to provide an optimal amount of ticket sales in response to advertising dollars spent. This optimal search marketing campaign is based on choosing effective allocation of ad dollars across the various search engines, as well as selecting appropriate keywords and bid strategies for placement on the search result page for Internet users.

In determining the optimal strategy, the case presents background information on the airline industry as well as the Internet search options available at the time, including Google, Microsoft MSN, Yahoo!, and Kayak. Additionally, background information is provided on SEM and its associated costs and means of measuring the successfulness of each marketing effort. The case illustrates how one must first determine the key performance indicators for the project to guide analysis and enable comparison of various SEM campaigns. Cost per click and probability to produce a sale differ among publishers. Therefore, using a portfolio application model's quadrant positions can be used to determine optimal publisher strategies. Additionally, pivot tables help illustrate campaigns and strategies that have historically been most successful in meeting Air France's target Internet sales. Multiple recommendations on how Media Contacts can assist Air France in improving its SEM strategy can be derived from the data provided.

Students learn how to optimally leverage the Internet in generating customer sales in a cost-effective manner. Students will analyze and manipulate a variety of data using pivot tables to determine optimal strategies for obtaining maximum total online bookings through the various online channels available. Using a portfolio application model, students can determine an optimal publisher strategy and complete copy improvement analysis.

Chris Barnett, director of global business solutions for Rand McNally, was deliberating how Rand McNally should respond to the emergence of wireless technologies for its traditional business of providing static maps and route-planning services. As maps became electronic, interactive, mobile, and enhanced with value-added features, Rand McNally's mapping business was gravely threatened. The opportunities for Rand McNally weren't obvious, and the pace at which wireless technology would disrupt its traditional business was also unclear. Barnett was considering three opportunities: syndicate Rand McNally's brand and mapping content to popular Web sites, become a provider of value-added services to businesses, or focus on automobile manufacturers and try to forge relationships for providing in-car mapping services.

To discuss organizational design, potential responses to disruptive technologies, and market opportunity analysis in order to identify the kind of technology, organizational, and sales force restructuring required to align Rand McNally's organization with the new environment.

The learning outcomes are as follows: to understand and examine the strategies that help platforms fight competition and manage networks; to analyse the role of platform governance in the management of the networks and partners’ trust; and to evaluate the strategic risks of disintermediation and multi-homing firms face while trying to sustain profits and capture value.

The case presents the dilemma faced by Deepinder Goyal, the young founder and CEO of Zomato in formulating the growth strategy for its food delivery platform, struggling to retain its market leadership position amid intensifying competition and other challenges during the COVID-19 pandemic. Zomato has become a public company with an IPO announced in mid of July 2021. Therefore, there is growing expectation for profitability among its shareholders and investors considering tailwinds of COVID-19 crisis, which have given the push towards adoption of food delivery among the customers. This has also resulted in increased competition in the industry. On other hand, there is growing dissatisfaction among its restaurant partners who have been hit hard by COVID-19 and struggling for survival. CEO Deepinder has to find how he will ensure the long-term growth for Zomato to tap the growing food delivery market in India and regain its restaurant partner’s trust.

The case is intended for post-graduate courses (MBA, PGDM) on digital business strategy or strategic management of technology-oriented businesses. The case can be used to understand the nature of competition and different strategies for platform-based businesses in the digital world. The case can also be used to study the role governance can play in efficient value creation and capture on the platform by the partner entities. Finally, the case also highlights how are platform businesses are coping with the Covid challenge. There are no specific prerequisites but knowledge on basic strategy concepts and platform business concepts will be good for better understanding. Level of difficulty is medium.

Teaching notes are available for educators only.

CSS 11: Strategy.

After a successful transition from a projects-based IT business services company to a platform-driven analytics company, Saama's core leadership team gathered in 2017 to brainstorm the next phase of its growth. The year before, the team had decided to narrow its target market to the life sciences vertical. Saama now had to decide how to execute on this focused strategy by choosing a growth pathway within the life sciences vertical. Saama's leadership team was considering three alternatives: acquiring new customer accounts, developing existing customer accounts, or developing new products by harnessing artificial intelligence (AI) and blockchain technologies. The team had to evaluate these growth pathways in terms of both short- and long-term revenue potential, as well as their potential for sustaining Saama's competitive advantage.

Uber had pioneered the growth and delivery of modern ridesharing services by leveraging the explosive growth of technology, GPS navigation, and smartphones. Ridesharing services had expanded across the world, growing rapidly in the United States, China, India, Europe, and Southeast Asia. Even as these services expanded and gained popularity, however, the pickup experience for drivers and riders did not always meet the expectations of either party. Pickups were complicated by traffic congestion, faulty GPS signals, and crowded pickup venues. Flawed pickups resulted in rider dissatisfaction and in lost revenues for drivers. Uber had identified the pickup experience as a top strategic priority, and a team at Uber, led by group product manager Birju Shah, was tasked with designing an automated solution to improve the pickup experience. This involved three steps. First, the team needed to analyze the pickup experience for various rider personas to identify problems at different stages in the pickup process. Next, it needed to create a model for predicting the best rider location for a pickup. The team also needed to develop a quantitative metric that would determine the quality of the pickup experience. These models and metrics would be used as inputs for a machine learning.