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Molly Madziva, who was born in Zimbabwe, was sent by her family to the USA to attend college. When she graduated in 2000 there were no jobs for her in Zimbabwe, as the economy was among the weakest in the world. While working as a software engineer at Bell Labs in New Jersey she decided that she wanted to help the people in her village of Macheke, the majority of who were farmers. Her idea would be an ambitious one. Molly called this the Macheke Sustainability Project. Molly met with various stakeholders who had an interest in the project. Following a thorough situation analysis and the formulation of a list of strategic initiatives, the major decision that she was left with was how to most effectively go about handling the implementation of the project. Her options included: a project within the Institute for Global Understanding at Monmouth University where she was enrolled as a graduate student; a non-profit business located in the USA; a non-governmental organization (NGO) located in Zimbabwe; and a private business in Zimbabwe. Each of these options had clear benefits. Molly was torn, however, as to which she should choose.

Resource-based view (RBV) theory (Barney, 1991; Barney and Mackey, 2016; Nagano, 2020) states that a firm’s tangible and intangible resources can represent a sustainable competitive advantage (SCA), a long-term competitive advantage that is extremely difficult to duplicate by another firm, when it meets four criteria (i.e. not imitable, are rare, valuable and not substitutable). In the context of this case, we believe there are three sources of SCA to be discussed using RBV – the major league soccer (MLS) team player roster, the use of artificial intelligence (AI) technologies to exploit this roster and the league’s single-entity structure: • MLS players: it has been widely acknowledged that a firm’s human resource talent, which includes professional soccer players (Omondi-Ochieng, 2019), can be a source of SCA. For example, from an RBV perspective, a player on the Los Angeles Galaxy roster: > cannot play for any other team in any other league at the same time (not imitable and are rare), > would already be a competitive player, as he is acquired to play in the highest professional league in the country (valuable) and > it would be almost impossible to find a clone player matching his exact talent characteristic (not substitutable) anywhere else. Of course, the roster mix of players must be managed by a capable coach who is able to exploit these resources and win championships (Szymanski et al., 2019). Therefore, it is the strategic human resource or talent management strategies of the professional soccer team roster that will enable a team to have the potential for an SCA (Maqueira et al., 2019). • Technology: technology can also be considered a source of SCA. However, this has been a source of contention. The argument is that technology is accessible to any firm that can afford to purchase it. Logically, any MLS team (or for that matter any professional soccer team) can acquire or build an AI system. For many observers, the only obvious constraint is financial resources. As we discuss in other parts of the case study, there is a fan-based assumption that what transpired in major league baseball (MLB) may repeat in the MLS. The movie Moneyball promoted the use of sabermetrics in baseball when making talent selection (as opposed to relying exclusively on scouts), which has now evolved into the norm of using technology-centered sports analytics across all MLB teams. In short, where is the advantage when every team uses technology for talent management? However, if that is the case, why are the MLB teams continuing to use AI and now the National Basketball Association (NBA), National Football League (NFL) and National Hockey League are following suit? We believe RBV theorists have already provided early insights: > “the exploitation of physical technology in a firm often involves the use of socially complex firm resources. Several firms may all possess the same physical technology, but only one of these firms may possess the social relations, cultural traditions, etc., to fully exploit this technology to implementing strategies…. and obtain a sustained competitive advantage from exploiting their physical technology more completely than other firms” (Barney, 1991, p. 110). • MLS League Single-Entity Structure: In contrast to other professional soccer leagues, the MLS has one distinct in-built edge – its ownership structure as a single entity, that is as one legal organization. All of the MLS teams are owned by the MLS, but with franchise operators. The centralization of operations provides the MLS with formidable economies of scale such as when investing in AI technologies for teams. Additionally, this ownership structure accords it leverage in negotiations for its inputs such as for player contracts. The MLS is the single employer of all its players, fully paying all salaries except those of the three marquees “designated players.” Collectively, this edge offers the MLS unparalleled fluidity and speed as a league when implementing changes, securing stakeholder buy-ins and adjusting for tailwinds. The “socially complex firm resources” is the unique talent composition of the professional soccer team and most critically its single entity structure. While every team can theoretically purchase an AI technology talent management system, its application entails use across 30 teams with a very different, complex and unique set of player talents. The MLS single-entity structure though is the resource that supplies the stability required for this human-machine (technology) symbioses to be fully accepted by stakeholders such as players and implemented with precision and speed across the entire league. So, there exists the potential for each MLS team (and the MLS as a league) to acquire SCA even when using “generic” AI technology, as long as other complex firm factors come into play.

This case relied on information that was widely reported within media, press interviews by MLS officials, announcements by various organizations, journal articles and publicly available information on MLS. All of the names and positions, in this case, are actual persons.

MLS started as a story of dreaming large and of quixotic adventure. Back in 1990, the founders of the MLS “sold” the league in exchange for the biggest prize in world soccer – the rights to host the 1994 Fédération Internationale de Football Association World Cup before they even wrote up the business plan. Today, the MLS is the highest-level professional men’s soccer league competition in the USA. That is a major achievement in just over 25-years, as the US hosts a large professional sports market. However, MLS has been unable to attract higher broadcasting value for its matches and break into the highest tier of international professional soccer. The key reason is that MLS matches are not deemed high quality content by broadcasters. To achieve higher quality matches requires many inputs such as soccer specific stadiums, growing the fan base, attracting key investors, league integrity and strong governance, all of which MLS has successfully achieved since its inception. However, attracting high quality playing talent is a critical input the MLS does not have because the league has repeatedly cautioned that it cannot afford them yet to ensure long-term financial sustainability. In fact, to guarantee this trade-off, the MLS is one of the only professional soccer leagues with an annual salary cap. So, the question is: how does MLS increase the quality of its matches (content) using relatively low cost (low quality) talent and still be able to demand higher broadcast revenues? One strategy is for the MLS to use AI playing technology to extract higher quality playing performance from its existing talent like other sports leagues have demonstrated, such as the NFL and NBA. To implement such a radical technology-centric strategy with its players requires the MLS to navigate associated issues such as human-machine symbioses, risking fan acceptance and even altering brand valuation.

The case is written and designed for a graduate-level (MBA) class or an upper-level undergraduate class in areas such as contemporary issues in management, human resource management, talent management, strategic management, sports management and sports marketing. The case is suitable for courses that discuss strategy, talent management, human resource management and brand strategy.

Social implications are as follows: social activism; girls education; collaboration; collective action; and change agent.

Learning outcomes are as follows: evaluate the role of a change agent in a nonprofit organization; understand collaborative partnerships in a nonprofit organization; examine how a nonprofit organization is promoting education in conflict-affected countries; understand the importance of education for girls as a basic human right; understand and discuss the threats to girls’ education in conflict-affected countries; analyze the role of Malala Yousafzai in supporting girls’ education globally; identify the challenges unique to educating girls; and explore steps that Yousafzai needs to take to ensure girls have equal access to the knowledge and skills they need to learn and lead in a world affected by the pandemic and climate change.

The case discusses social activist Malala Yousafzai’s (She) diligent efforts to promote girls’ education in conflict-affected regions globally through her not-for-profit organization Malala Fund. Co-founded in 2013, Malala Fund worked to ensure every girl globally could access 12 years of free, safe, quality education. The fund worked towards this goal by building creative partnerships and investing in its global network of education activists and advocates fighting for girls’ education in communities where most girls missed out. Malala Fund supported girls’ education programs in countries such as Pakistan, Afghanistan, Nigeria, India, Brazil, Ethiopia, Turkey and Lebanon. The Fund’s projects were aimed at addressing gender norms, promoting the empowerment of girls through education, imparting gender-sensitive training for teachers and raising awareness about the need for girls’ education. In 2016, the fund created the Education Champion Network to support the work of local educators and advocates to advance.

Post-graduate level students.

Teaching notes are available for educators only.

CCS 11: Strategy.

Communication Solutions (CS), a woman-owned business, experienced fast growth at its inception, and then found itself slowing after the mid-2000s recession. The firm provides consulting services, primarily to government agencies. The owners have brought the business to sales of about $10.5 million in 2012, but revenues declined following that peak year because of cutbacks in government spending and founder Jennifer Madison’s detachment from the business. Even though they recognize that it may not be an ideal time to sell, they are tired of running the business and want to sell now, as long as they can pay off their debts.

This case was researched through multiple interviews with Mark and Jennifer, who provided all of the financial data and background. All financial statements given in the case provide actual CS numbers. The name of the company and the names of the owners have been changed, at their request to disguise the company. At the time this case was written, the owners were in negotiation with a potential bidder, and did not want their names or their company name to be used. Market information and information about comparable companies was researched using publicly available financial data bases.

This case has the potential to be used in a variety of classes, depending on what the instructor wishes to emphasize. The author uses the case as a valuation case in a corporate finance class (suitable for undergraduates or MBAs), allowing students practice in discounted cash flow valuation and comparable multiples valuation. It could be used in an investments class which teaches business valuation, particularly in teaching valuation using market multiples. The case could be used in an entrepreneurial finance class. The author uses this case to illustrate the difficulties of business valuation with messy (but real) data.

This case explores small business valuation and exit strategies for founders. Students can put themselves in the position of small business owners who are ready to exit. Students should value the firm using discounted cash flow and multiples valuation, which includes making assumptions about the future growth of the firm. While there is likely to be reasonable agreement on the “as is” valuation, there may be great variation concerning the assumptions and valuations of the company as it could be. Students can discuss (and implement) adjustments made when using large company comparables to value a much smaller company.

This case considers the buyout of Panera Bread from the perspective of a private equity fund. In early 2017, KLG Managing Director Tom Denning is considering a leveraged buyout of Panera Bread, a rapidly growing fast-casual restaurant company. A surprising Bloomberg News story signals that the deal process is broadening and KLG will have to act quickly if it hopes to buy Panera Bread. Students assume the role of Tom Denning as he prepares an investment recommendation for KLG's investment committee. In doing so, students are required to consider a very large and expensive investment. Students are challenged to create an investment recommendation by performing due diligence, determining additional questions to ask, and pricing a buyout bid that incorporates an optimal capital structure and meets KLG's return requirements. The Panera Bread case is designed to give students insight into the private equity investment process.

Mary Kay is one of the best-known direct sellers of women's cosmetics in the world. Its channel strategy is to use independent beauty consultants, who are independent distributors, to sell directly to consumers. Its compensation plan is multilevel, providing commissions to distributors on their own sales as well as the sales of the distributors they recruit. At the time of the case, the company is grappling with a well-established change in consumer behavior—the decline of the stay-at-home mom as she returns to the workforce—combined with the opportunities offered by Internet selling. Focuses on the company's efforts to move with consumer demand and behavior, while remaining true to its core goal of “Improving Women's Lives.” Discusses ways Internet technology can be used throughout the company's channel and supply chain structure, not just as a route to market.

This case is about Kija Kim, a Korean born founder and CEO of Harvard Design and Mapping Inc. (HDM). Founded in 1988, HDM is a cutting-edge GIS firm with $5 million in revenue and 35 employees in their Cambridge, MA and Washington D.C. offices. Through Kija Kim's leadership, HDM has become a significant niche player in homeland security and disaster relief. The case ends in fall 2005 just after HDM provided Hurricane Katrina mapping support, and Kija is nominated for the SBA Small Business Person of the Year. This case explores the intersection between cultural heritage, leadership effectiveness and organizational behavior. It particularly notes Kija's ability to turn her immigrant female minority status into a business advantage. This strength coupled with her ethos of care and ability to network in all walks of her life contributes to her distinctive and integrated leadership style. Definitions of leadership success and implications for decision making are also highlighted.

The subject areas are entrepreneurship, start-up ventures and business strategy.

The case is appropriate for undergraduate and graduate MBA.

Shikhar Veer Singh (Singh), a post graduate in Medical Biotechnology, quit a cushy corporate job to start his own food venture WoknStove Foodworks Pvt. Ltd. (WSFL) in October 2015. WSFL sold the ubiquitous popular Indian snack food “Samosas” under the brand name of “Samosa Singh”. “Samosa” – a deep fried triangular in shape with conical edges crispy wrap with variety fillings of potatoes/vegetables – was part of unorganized sector and sold by small shops and road-side hawkers. Singh spotted an opportunity to “brand” the “Samosas” that as well was gaining momentum in the international convenience food markets. The company set up a central kitchen near Electronic city, Bangalore, and started experimenting with different fillings. In February 2016, WSFL opened its first quick service restaurant (QSR) in Electronic city, Bangalore. It was an instant hit with consumers of all age groups. Gradually, the company started supplying bulk orders to various other customer segments such as corporate customers, schools and movie theatres/event stalls, that resulted in revenue growth. By January 2017, his monthly annual revenues amounted to INR […] Singh had ambitious plans to expand his business from a single QSR to 15 QSRs across the city by 2018. However, to cater to the increasing demands and support his expansion plans, he was yet to find out the most suitable back-end processes. He had adopted few standard operating procedures (SOPs) for quality operations and implemented 30 per cent of automation for backend processes at his central kitchen. Singh was aware of the automated machinery available in international markets that had conveyor belt arrangements where one could place the flour dough and filling consecutively to get the end product in a shape, unlike the shape of the Indian “Samosas”. The triangular shape with conical edges of the Indian “Samosas” was of utmost importance for the Indian consumers, as the shape associated them with the favourite snack, the “Samosas”. Singh preferred the method of manual filling to maintain the shape and decided to focus on increasing the shelf life of the “Samosas” instead. He felt that an increased shelf life would better equip him to cater the increased market and seasonal demands. However, the question was that whether this was a feasible option to support his ambitious expansion plans (with only 30 per cent automation)? Was Singh’s thinking right with respect to the business operation? More importantly, whether WSFL venture would be able to make an attractive business proposition for investments from any future institutional/angel investor? Singh’s mood turned reflective as he pondered on the above questions.

The case is structured to discuss the structure of Indian QSR market and factors contributing to its growth, evaluate WSFL’s ability to leverage the Indian QSR market potential, its strengths and shortcomings, to highlight the steps of consumer decision making process in terms of selection of a QSR and discuss WSFL’s business model and its future sustainability.

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

By any measure, Chipotle Mexican Grill was a success story in the restaurant business. It grew from one location in 1993 to over 2,000 locations by 2016 and essentially created the fast casual dining category. Its stock appreciated more than 1,000% in the ten years following its 2006 IPO.

However, after more than 20 years without a major reported food safety incident, Chipotle was revealed as the source of multiple outbreaks of illness from norovirus, salmonella, and E. coli that sickened nearly 600 people in 13 states in 2015. The company closed stores, spent several months under investigation by the U.S. Centers for Disease Control and Prevention (CDC) and other health organizations, and faced a criminal investigation in connection with the incidents.

After a much-publicized closing of all of its stores on February 8, 2016, and numerous changes to its food sourcing and preparation practices, Chipotle tried to win back customers with dramatically increased advertising and free food promotions.

However, on April 26, the chain announced its first-ever quarterly loss as a public company. Same-store sales for the first quarter were 29.7% lower than in the previous year. Operating margins fell from 27.5% to 6.8% over the same period, and the company's share price was down 41% from its summer 2015 high.