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The recycling system was in desperate need of innovation in North America in 2020. The average person was generating 12 times their body weight in landfilled trash annually, and the equivalent to a dump truck full of plastic waste was entering the world's oceans every minute. This crisis prompted Ainslie Simmonds and Mark Manley to develop MeCycle, an innovative, technology-enabled platform to help change consumer behaviour and increase recycling rates. This case examines consumer behaviour with regards to recycling, explores barriers to recycling, describes MeCycle’s business model, and estimates the potential environmental and economic gains from hypothetically implementing the MeCycle platform in London, Ontario, Canada.

The recycling system was in desperate need of innovation in North America in 2020. The average person was generating 12 times their body weight in landfilled trash annually, and the equivalent to a dump truck full of plastic waste was entering the world's oceans every minute. This crisis prompted Ainslie Simmonds and Mark Manley to develop MeCycle, an innovative, technology-enabled platform to help change consumer behaviour and increase recycling rates. This case examines consumer behaviour with regards to recycling, explores barriers to recycling, describes MeCycle's business model, and estimates the potential environmental and economic gains from hypothetically implementing the MeCycle platform in London, Ontario, Canada.

Although foreignness can bring both benefits and costs to a business, much of the literature has focused on the liability of foreignness (LOF), while relatively little attention has been paid to the positive side. Despite the presence of LOFs, foreign companies may accrue some unique advantages from their foreign status, which are referred to as assets of foreignness (AOFs). Drawing upon social-capital theory and institutional theory, this article examines the issue of LOFs versus AOFs in the context of the informal networks in Korea and explores how foreign companies can manage their weaknesses in host-country-specific informal networks to create value from their foreignness. We discuss two practical strategies, reactive and proactive strategies, that can be used by foreign companies. While these two strategies can be pursued in parallel, this article suggests that foreign companies should prioritize pursuing proactive strategies. This article contributes to a more nuanced understanding of the role of foreignness in the international business context and provides practical insights into how foreign companies can leverage their foreign status in developing their own informal networks in Korea.

In February 2021, political turmoil had engulfed Myanmar following a military coup under which elected leader Aung San Suu Kyi was jailed after her party won a landslide victory in the elections. CEO and co-founder of Daung Capital (Daung), a microfinance institution (MFI) in Myanmar, Leon Qiu recalled the years before the coup, when inclusive finance businesses like his had just begun to flourish. Daung had offered a variety of loan products in Myanmar since its inception in 2017. Its products included short-term loans for purchasing motorbikes, short-term loans to salaried workers for purchase of everyday utility items, and educational loans to students from poorer households. In 2019, Daung had launched a new loan product for farmers. Unlike other loan products, the loan scheme for farmers did not entail regular repayments. Instead, the farmers were expected to repay the loan as a lump sum after the harvest. Careful credit risk assessment of the target customer base was a key criterion in designing a loan product for farmers. Ethical obligations and decision-making were important considerations as well. Qiu pondered over the various constraints around which the farmer loan product had been constructed and how it could be improved. How could Qiu and his team assess the credit risks associated with the farmer loan product? What strategies could they implement to control the credit risks associated with farmer loans? Could they use machine-learning algorithms to assess the credit risks? The case illustrates (1) the various challenges faced by an MFI in assessing credit risk of agricultural borrowers (mainly farmers) (2) the dynamics of the MFI sector in Myanmar (3) credit risks presented by rural lenders. The case can be used in undergraduate, postgraduate and executive education classes to teach concepts on credit risk management in microfinance for emerging markets.

Set in September 2021, the case traces the digital transformation of FoodXervices Inc, a Singapore SME operating in the food distribution industry. The case essays the challenges faced by Nichol as a leader helming the digital transformation and how the transformation helped the company redefine its value proposition to the stakeholders. To customers, it pivoted from being a distributor to a solution provider; to the labour market, it had become a foodtech company attracting savvy university graduates as employees; to the F&B community, it had become an incubator fostering innovations. However, Nichol wanted more value to justify the company's investment in digital technology and futuristic application. In addition, she wanted the technology to improve the business metrics by improving sales and margins.

Set in May 2021, this case describes the journey of transformation Hai Sia Seafood (Hai Sia), a Singapore-based seafood company, embarked upon five years earlier. Hai Sia, a family business established forty-five years earlier, supplied high quality, fresh, and processed seafood at competitive prices for domestic consumption in Singapore. However, the seafood processing industry in the city-state, including the port, was woefully backward. Hai Sia operated a manual processing plant that was twenty years old, and relied completely on labour intensive work processes, even though digitisation was on the rise in the country and consumers were increasingly migrating online in their buying behaviour. The company faced many challenges such as quota constraints on the number of foreign workers it could hire, inconsistency in quality due to human error, low productivity, and more importantly, the changing profile of its customer base. Hai Sia undertook many steps to transform its operations, including plant renovation and automation, digitisation of work processes, expansion into e-commerce, launch of a consumer brand, and product development for the retail market. The results were promising and the business grew from 1800 tons in 2015 to 2500 tons in 2020. However, the considerable corresponding investments to support these initiatives had adversely impacted the company's profitability. Ang Junting, the deputy director, knew that if he were to spend more time and resources in modernising the business, the senior management would need to be convinced about the returns that these investments would eventually bring. Moreover, he wondered if going forward, a similar business model that centred on automation, upskilling, training, and consumer retail could be successfully replicated in the neighbouring Southeast Asian economies.

Analysts have often compared Digital Transformation to an iceberg and a company embarking on it to a ship trying to manoeuvre the iceberg. Some facets of the transformation are easily visible, while others are under the water and difficult to identify and manage. Douglas Chia, Managing Director of g&m Insurance, was well aware of this theory when he embarked on his firm's digital transformation journey. Chia had implemented small digital initiatives in his organisation in 2019, and was able to see significant revenue growth of 30% in 2020, despite a sluggish market because of the Covid-19 pandemic. Chia wanted to continue driving his firm's growth and positive revenue trend, specifically with digital solutions that targeted the evolving insurance market. He set goals to embark further on the digital transformation journey, by introducing an online portal providing online insurance products and an aggregator platform by the end of 2021. The above goals were in tandem with the developments in the insurance industry, as more and more firms were introducing online insurance products and offering them directly to consumers, thus eliminating the need for an intermediary agent or broker. Amidst such changing market conditions, brokerage firms like g&m had no option but to transform their business models to compete in the market. Chia wanted to continue using his agent based business model for existing customers, and introduce online solutions to target new market segments. What strategies could Chia implement to further g&m's digital transformation journey to expand his business?

As organizations accelerate digital transformation with mobile devices, cloud services, social media, and Internet of Things services, cybersecurity has become a key priority in enterprise risk management. While improving cybersecurity leads to higher levels of customer trust and increased revenue opportunities, rapidly evolving data protection and privacy regulations have complicated cybersecurity management. Against the backdrop of rapidly rising cyberbreaches and the emergence of novel cybersecurity technologies such as machine learning and artificial intelligence, this article introduces a cyber risk management framework, discusses a cyber risk assessment process, and illustrates a continuous improvement of cybersecurity performance and cyberinvestment cost analysis with a real-world cybersecurity example.

It was June 2020, in the midst of the COVID-19 pandemic, and Frances Edmonds, head of sustainable impact at HP Canada Co., the Canadian subsidiary of HP Inc. (HP), was continuing HP’s decades-long pursuit of sustainable impact. HP had worked nearly two decades with strategic partners like Lavergne Groupe to redesign its products and make plastic circular. HP was now committed to using 30 per cent post-consumer recycled plastic across its personal systems and printers by 2025. However, decreasing commodity prices during the COVID-19 pandemic, global supply challenges, and lowered global collection of recycled content could potentially undermine HP’s recycling efforts and goals. Edmonds was considering possible strategic, tactical, and operational actions to cope with the situation and sustain HP’s aspirations. Would HP’s circular supply chain remain viable and competitive?

It was June 2020, in the midst of the COVID-19 pandemic, and Frances Edmonds, head of sustainable impact at HP Canada Co., the Canadian subsidiary of HP Inc. (HP), was continuing HP's decades-long pursuit of sustainable impact. HP was now committed to using 30 per cent post-consumer recycled plastic across its personal systems and printers by 2025. However, decreasing commodity prices during the COVID-19 pandemic, global supply challenges, and lowered global collection of recycled content could potentially undermine HP's recycling efforts and goals. Edmonds was considering possible strategic, tactical, and operational actions to cope with the situation and sustain HP's aspirations. Would HP's circular supply chain remain viable and competitive?

In March 2019, Boeing's 737 MAX aircraft was grounded across the globe following its second crash in five months. Investigations concluded that the sensor in the planes' Maneuvering Characteristics Augmentation System (MCAS) had failed, leading both aircraft to nosedive downward, crashing and killing all aboard. The public was confused as to how this engineering error occurred, given Boeing's strong history of aerospace achievements. The case traces the main developments in the aircraft manufacturing industry and Boeing's organizational changes over time. How could these changes have affected events leading up to the two 737 MAX crashes?

Spreadsheet to accompany product 9B20N017.

Spreadsheet for product 8B20N017.

On October 27, 2017, the share price of McKesson Corporation and two other major US pharmaceutical distributors dropped by 7–12 per cent over only a few days. The stock price drop was fuelled by reports that Amazon Inc. had quietly acquired wholesales pharmacy licences in 12 US states and, a short time later, formed an independent venture with Berkshire Hathaway Inc. and JP Morgan Chase & Co. to improve the cost and quality of health care for the US employees of all three companies. These two notable events in the US pharmaceuticals market did not go unnoticed by a group of students enrolled in a value investing class, who wondered if it was possible for Amazon Inc. to disrupt the US health care industry, or if the market was overreacting to the two reports. Was McKesson Corporation’s future in the pharmaceutical distribution business in jeopardy, or was its stock suddenly in a favourable buy position?

On October 27, 2017, the share price of McKesson Corporation and two other major US pharmaceutical distributors dropped by 7-12 per cent over only a few days. The stock price drop was fuelled by reports that Amazon Inc. had quietly acquired wholesales pharmacy licences in 12 US states and, a short time later, formed an independent venture with Berkshire Hathaway Inc. and JP Morgan Chase & Co. to improve the cost and quality of health care for the US employees of all three companies. These two notable events in the US pharmaceuticals market did not go unnoticed by a group of students enrolled in a value investing class, who wondered if it was possible for Amazon Inc. to disrupt the US health care industry, or if the market was overreacting to the two reports. Was McKesson Corporation's future in the pharmaceutical distribution business in jeopardy, or was its stock suddenly in a favourable buy position?

Student spreadsheet to case W20488

Machine learning holds great promise for lowering product and service costs, speeding up business processes, and serving customers better. It is recognized as one of the most important application areas in this era of unprecedented technological development, and its adoption is gaining momentum across almost all industries. In view of this, we offer a brief discussion of categories of machine learning and then present three types of machine-learning usage at enterprises. We then discuss the trade-off between the accuracy and interpretability of machine-learning algorithms, a crucial consideration in selecting the right algorithm for the task at hand. We next outline three cases of machine-learning development in financial services. Finally, we discuss challenges all managers must confront in deploying machine-learning applications.

This article provides an overview of social media analytics for managers that seek to utilize the practice for social media intelligence. Currently, managers are challenged to analyze an abundance of social media data but lack a framework within which to do so. Toward this end, this article presents a simple typology of social media analytics for enterprises. It also discusses various analytics methods for social media data. Then, this article discusses management processes of social media analytics for enterprises. An illustration of social media analytics is provided with real-world consumer review data. Finally, four challenges are discussed.

Fintech brings about a new paradigm in which information technology is driving innovation in the financial industry. Fintech is touted as a game changing, disruptive innovation capable of shaking up traditional financial markets. This article introduces a historical view of fintech and discusses the ecosystem of the fintech sector. We then discuss various fintech business models and investment types. This article illustrates the use of real options for fintech investment decisions. Finally, technical and managerial challenges for both fintech startups and traditional financial institutions are discussed.

Big data represents a new technology paradigm for data that are generated at high velocity and high volume, and with high variety. Big data is envisioned as a game changer capable of revolutionizing the way businesses operate in many industries. This article introduces an integrated view of big data, traces the evolution of big data over the past 20 years, and discusses data analytics essential for processing various structured and unstructured data. This article illustrates the application of data analytics using merchant review data. The impacts of big data on key business performances are then evaluated. Finally, six technical and managerial challenges are discussed.