Could rice become as crucial as petrol in the fight against climate change? In 2023, Nguyen Duy Thuan, General Director of Loc Troi Group (Loc Troi) Vietnam, was sceptical. His company, the largest rice producer in the country, faced a pivotal moment in its journey. Following a successful pilot program involving 1,000 farmers, the company had started scaling sustainable rice production (SRP). Sustainable rice had much lower emissions and used fewer resources than traditional rice production, which accounted for 12% of global methane emissions and significantly threatened the climate. The pilot had reduced pesticide use by 12%, water use by 25%, greenhouse gas emissions by a third, and flooding and straw burning by using organic treatments. It had also lowered production costs and increased profit margins by 18%. But despite such demonstrable benefits, Loc Troi continued to struggle to convince farmers to grow sustainable rice, which constituted only 5% of its total export volume, due to the time-consuming and costly new practices. Scaling sustainable rice required large investments and without government grants, could be financially draining for the company. Loc Troi's other businesses, like vegetable seeds and fertilisers, were also profitable, so over-investing in rice could hinder their growth. Thuan pondered on how to scale sustainable rice and tap into future demand with Loc Troi's expertise.

The case is set in September 2023, and talks about the energy transition of the oil and gas industry in context to ExxonMobil (Exxon), which has seen continued backlash from media and climate activists on its stance on climate change, strategies towards pivoting its core business towards more sustainable practices and moving away from fossil fuel energy that contributes significantly to global warming. While many oil and gas companies have increasingly opted to investing in renewable forms of energy, Exxon has instead focused on investing in carbon capture and storage (CCS) technology, and other alternate forms of energy like hydrogen and biofuels. Exxon had also introduced Net Zero pledges, but industry analysts continued to question the company's stance and strategies and its persistent focus on oil and gas. Was chasing Net Zero the right strategy for Exxon moving forward? Given its predominant involvement in oil and natural gas, was it strategic to persist in prioritizing oil demand alongside lower emission initiatives and transition investments? Was its existing strategy sufficient to help the conglomerate reinvent itself in a competitive and rapidly changing energy market?

This case discusses Toblerone chocolates' pricing strategy at duty-free shops in international airports and entails 15-20 minutes of reading time. It analyses how the world-renowned Swiss chocolate brand Toblerone created a successful market strategy for duty-free shopping, and why it is considered one of the most iconic brands in duty-free stores worldwide. Central to the case is the assessment of Toblerone's variable pricing strategy across different airports, and whether duty-free prices are lower than local store prices. What is the rationale behind Toblerone's pricing strategy? Is duty-free shopping actually cheaper? Adding depth to the analysis, the case also evaluates the pricing strategy of other products such as duty-free favourites like alcohol brand Johnnie Walker and electronics brand Apple iPhone, providing valuable comparisons. The Teaching Note supplements the case by comparing Toblerone prices to Dairy Milk, fostering a more comprehensive discussion. The goal is to offer insights into Toblerone's strategic approach to pricing within the unique context of duty-free markets and to stimulate thoughtful discussion on its sustainability and effectiveness in meeting consumer expectations.

In early 2023, Claire Chiang, co-founder of Banyan Tree Group (Banyan Tree), a Singapore-based multinational hospitality brand with several hotels and resorts across the globe, was contemplating growth plans for the company. Banyan tree was aiming to double its existing portfolio to 100 hotels and resorts by 2025, while remaining competitive in a market dominated by large international players, and staying true to its brand philosophy of creating shared value (CSV). Banyan Tree had entered the market with unique proposition of providing culturally rich and unique destination experiences with an innovative 'pool villa' concept to luxury travellers while focussing on sustainability. The company had also concentrated on a 'Responsible Leadership' approach to drive growth and business diversification. Could Banyan Tree expand rapidly while staying true to its core values of CSV and sustainable development? Could it continue to maintain its competitive advantage when other players were also increasingly adopting sustainable development goals? The case can be used in Strategy and Finance courses that teach Competitive Strategy, Creating Shared Value (CSV), and Sustainable Business as a business strategy in graduate and executive education classes.

The case is set in April 2023, soon after DBS Bank Limited (DBS) reported a 20% net profit growth of US$6.02 billion. The bank's CEO Piyush Gupta had attributed this growth to the company's continuing digital transformation journey that had started more than a decade ago. Central to this journey was the bank's adaptation of Artificial Intelligence (AI), to improve and diversify products and services. To become AI-fuelled, DBS had created a "Data First" culture and hired hundreds of technology professionals to build its technology capabilities. In addition, the bank had set aside substantial budgets to allow for experimentation, motivated individual departments to build and deploy AI-based applications, implemented an automation strategy to guide solution building, and embedded AI into nearly every part of the customer journey. Prior to the transformation, DBS was sometimes irreverently referred to as 'Damm Bloody Slow' due to its poor customer service, but had emerged as a customer-savvy, market-responsive, AI-fuelled company with more successes than failures, diversified lines of business, and dramatic growth in revenues. However, the financial services sector was seeing increased competition due to the entry of purely technology companies like Grab, PayPal, Alibaba, etc. with innovative solutions. How could DBS compete in a rapidly changing banking marketplace? Had the 'All in on AI' approach given the bank a competitive advantage? Could DBS's prior 10 years of successful efforts with digitalisation, analytics and AI position it to take advantage of the newest generation of Generative AI in an accelerated manner?

This social network data analysis case presents the scenario of the launch of a new version of a popular video game called 'Thrive in Space' by a gaming company. The company's Chief Marketing Officer Tina Lohn wants to run an influencer marketing campaign on social platform Twitch to reach its live streaming audience and promote the game. However, before running the campaign, Lohn and her team must select the right influencers for the campaign. Lohn has asked her team to conduct a social network analysis (SNA) to better understand the network of Twitch users and shortlist potential influencers based on various social network metrics. The case is accompanied by two datasets that contain a sample of real data of Twitch users, and allows students to conduct a social network analysis on this data to select the appropriate influencers. The case revolves around Lohn's dilemma of how to choose the right influencers. How can she use SNA to select the influencers? What social network metrics can help her identify the right influencers? What other strategies can she use for selecting influencers that can complement SNA? And, finally, how can she calculate the ROIs of working with the selected influencers?

This case study begins in October 2022, two years after Sophia and Eileen Goh, who were sisters, rebranded the footwear company to expand its customer base from baby boomers and Gen X to millennials and Gen Z. The footwear brand was originally positioned as a workwear brand, specifically to cater to women who had wide feet and suffered from bunions. Growth was steady in the first 20 years and was primarily driven by word-of-mouth. However, by 2020, the brand had lost its appeal to the millennials and Gen Z. In September 2020, the sisters embarked on an initial rebranding strategy by repositioning DMK as shoes for every occasion and milestone across a woman's lifetime journey. The rebranding effort was further strengthened by focusing on five pillars including supporting the female community, product diversification, reintroduction of DMK Care to enhance comfort of the shoes, introducing a new retail experience to provide immersive customer experience at the outlets and strengthening of DMK's digital capabilities. The Singapore footwear market was worth US$870 million in 2020 and was expected to grow to US$1,270 million by 2025. What else could DMK do to further elevate the brand and future prooffuture-proof the business?

This simulation case is meant to be used as a learning object for students to understand the various facets of the Resources, Events, Agents (REA) data model in designing accounting information systems. The case allows students to analyse the various entities in an REA data model, and identify associations between these entities and their cardinalities. There are two scenario examples provided in the simulation - 1) YY Frozen Yoghurt and 2) SMU Mart. The first simulation helps students understand the concepts of the REA data model, and the second simulation assesses students' understanding of the REA concepts and framework.

This case talks about the 3P (People Planet Profit) strategies of Ant Group backed MYbank, which was established as an online bank in China, as part of Alibaba's ecosystem, with the vision of providing inclusive finance services to SMEs and farmers in rural China. In April 2022, however, the Chinese economy was grappling with the after effects of the Covid-19 pandemic and macro-economic trends had predicted slower growth for the year. The aggregate net profit of China's commercial banks was expected to grow at around 10% in 2022, compared to 12.6% in 2021. However, despite the challenges, there was optimism at MYbank as the company had reported a year-on-year growth of 31.6% for the first quarter of 2022, with loans and advances for the first quarter totalling a staggering US$ 27 billion. Banking had traditionally always paid more attention to high-net-worth individuals, fewer accounts and more one-on-one relationships. MYbank however, had focussed on technology, innovation, quick transactions, large volume of low-income consumers, and lower operational costs to create a sustainable business model. However, ripple effects of the pandemic were plaguing its target customer segment - SMEs and farmers from low-income backgrounds in rural China - who were grappling with economic uncertainties. Could MYbank continue to adopt a low margin, high volume model like assembly line businesses to target large swathes of the rural population and generate profit in the process? Could MYbank become the McDonald's of digital banking in China?

Set in April 2022, this case delves into supply chain disruptions faced by 3M in and after the Covid-19 pandemic, and the strategies used by the company to cope with the challenges. The case begins by tracing the history of 3M as an 'Innovation Machine', and its internationalization strategy in its early years. It then talks about the company's regionalisation strategy, and complementary growth strategies like the 'Divide and Grow', 'Follow the Technology' and 'Renewal' tactics to expand and diversify internationally. It also talks about the digital transformation and the consolidated operating model, which the company embarked upon in 2019, to re-energise the company. In 2020, 3M faced massive supply chain disruptions amidst a 400% demand surge of N95 masks and personal protective equipment, and simultaneous closure of several manufacturing facilities worldwide. 3M continued to operate from manufacturing plants that were still open, with government support - in countries like Singapore - while facing resource and supply constraints and other uncertainties. To cope with the disruption, the company used several strategies like emergency response teams, 30/60/90-day cycles of supply management, additional supplier sourcing and airfreight for exporting finished goods. In 2022, even after the pandemic started to subside, supply chain disruptions continued to persist amidst increasing geopolitical tensions like the Russia-Ukraine war and a new surge of the pandemic in China. Given the prolonged and evolving supply chain disturbances, what could be the appropriate short-term and longer term strategies that 3M could implement to respond to such disruptions?

The case is set in May 2021 and talks about a Singapore-based small-medium enterprise decision science company called Blackbox (BB) and how it used conversational AI, human-centered design, and a technology innovation partner to design and develop a chatbot that helped its clients understand data insights with the language of everyday conversations. BB generated vast data through opinion surveys and complex market analyses for its clients. While dashboards and reports provided a glimpse into that data, these tools did not necessarily help clients make immediate data-driven business decisions. Analysts would spend time on the phone answering simple and often repetitive questions to explain the key findings. BB decided to build a chatbot that could handle natural language queries independently to reduce the time of live support calls and allow even non-specialized users to access data insights directly. The CEO, David Black, and his team, led by Chief Operating Officer, Saurabh Sardana, embarked on designing a conversational data platform to provide improved services to clients at scale. However, how could BB execute this idea efficiently without an internal technical team specializing in building chatbots? How could the company avoid the pitfalls of typical commercial chatbots that fail to engage users? How could Black and his team design a conversational data platform that efficiently imitated human-to-human conversations, which clients could use independently? Could this new platform help the company become a differentiator in the market?

The case is set in July 2020, when Lynk Biotech (Lynk), a pharmaceutical research company based in Singapore is facing the dilemma of designing new products from its existing transdermal platform which is a well-researched proven technology developed by the company. Lynk was a university spin-off focused on drug research, and had pivoted its business model to come up with over-the-counter topical cream products for the market. The company had followed the research publication route to gain visibility for its technology innovation and the clinical trial route to use its proprietary technology to develop products and bring them to market. All along, the company had relied on Open Innovation methods to build collaboration with local educational institutions to publish its research and help conduct clinical trials. However, the company faced significant challenges in expanding its market outside Singapore, as its products required expensive clinical trials and faced regulatory challenges in most countries. In late 2019, a local research firm with ties to a renowned university in Singapore had approached Lynk to collaborate on using its proprietary technology for a new product that it was designing. While sharing its technology with appropriate licensing measures could be a plausible approach for the company to expand its outreach, were there other avenues that Lynk could explore to expand its business? Was partnering with research organisations the right way forward? Had the clinical trial method been the right way of embarking on its Open Innovation journey?

This is a game simulation case on Machine Learning (ML) and can be used in the classroom to introduce to students the foundational concepts of ML. The case begins with a brief background on ML, its origins, the objectives of its usage across various industries, and ends with a future outlook on the relevance of ML. At the end of the case, a link to the game simulation is provided, which can be played by students in the classroom. The main topics covered in the game simulation include: • An introduction to ML • Different categories of ML algorithms including unsupervised, supervised and re-enforcement learning (based on the differences in the way they process the data for decision-making). • Identifying applications and use cases of ML

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.

This is a game simulation case on yield management for the hotel industry. Students play the role of the reservation manager and are allowed to make hotel bookings for consumers who want to book hotel rooms at the Inn or Out hotel. Students are encouraged to accept the bookings based on the principles of yield management. At the end of the game, students can see the amount of revenue that they have generated for the hotel based on the bookings that they have accepted and rejected. The game allows students to apply different strategies for high season and low season bookings. Penalties are applied to the revenue scores based on whether the rooms were overbooked or under booked. The case accompanying the game allows students to understand the concepts of yield management that they need to apply to play the game well and achieve higher scores. A separate set of settings in the game allows the instructor to adjust the various parameters of the game, and present consumers with different profiles, so as to assess the student's understanding of yield management strategies. The Teaching Note serves as a guide for the instructor to execute the game in the classroom for students, and to cover the basic concepts in yield management through the game.

It was April 2021, and Widjaja Suki, Director of Business Development at NetLink Trust (NLT), was contemplating on his firm's future growth and revenue prospects. NLT was the sole broadband fibre infrastructure provider in Singapore for the residential segment, and had played a key role in the country's Smart Nation initiative towards a digitally-led economy. The firm had relied on a regulatory asset base (RAB) funding model to finance its infrastructure, operations and services. However, it faced stiff competition in the non-residential segment, where telecom players with their own fibre were able to provide broadband services. As of 2020, NLT held an overwhelmingly dominant 91% share of the residential segment, but a far lower 35% share of the non-residential segment. While NLT was the only approved player for the residential market, its share in the segment was not 100%, as some of the residential customers from economically weaker sections had yet not availed broadband services. With limited growth prospects in residential and other segments, what growth strategies could NLT adopt in the coming years? How could the firm expand its business to drive more revenue? Was the RAB framework effective in delivering long-term sustainability for the firm?

Chinese electric vehicle (EV) company NIO had launched Battery as a Service (BaaS), in a competitive bid to reduce vehicle price and make its products more attractive to its consumers. By 2021, almost 40% of its consumer base had switched to using BaaS, and NIO had plans to expand its BaaS services further. BaaS offered four key benefits. Firstly, it reduced the price of the EV by about US$ 10,800. Secondly, it allowed consumers to do multiple battery swaps for a nominal US$ 152 monthly subscription fee. Thirdly, it allowed consumers to swap their batteries in a short time of 3 to 5 minutes, as opposed to 45 minutes recharge at a charging station. To support its BaaS program, NIO had installed 301 battery-swapping stations across China by July 2021, and had plans to complete 3000 swapping stations globally by 2025. Fourthly, BaaS supported a circular economy, as it potentially helped recycle batteries in a more controlled fashion, which could then be reused in other industries (like for solar panels in homes). However, NIO's BaaS entailed a few shortcomings despite its promise. Its implementation involved the construction of swapping stations, deployment of automated technology, and maintenance of battery stocks at stations, which was an expensive affair. Besides, technology for batteries had started to advance, and batteries could last longer in terms of miles travelled based on a single charge, reducing the need for frequent recharge at swapping stations. Given the scenario, was NIO's BaaS venture a sustainable business model? Could it provide NIO with a strong competitive advantage?

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?

Set in July 2021, this case talks about the launch and discontinuation of the very large aircraft, A380, by leading aircraft manufacturer Airbus. The development of the A380 had been motivated by two key factors - the projected market trend of increased hub-and-spoke travel and the success of Boeing 747 - a very large aircraft by Boeing. Although the A380 was the biggest passenger aircraft ever built, with avant-garde technology and reconfigurable design, it failed to succeed due to changing industry trends. Hub airports were witnessing increasing traffic congestion, and more and more airlines were switching to point-to-point travel to avoid hubs altogether. Demand for very large aircrafts like the A380 fell by almost 92% from 2010 to 2020, and Airbus had to make the harsh decision of shutting down the aircraft's production in 2021. The case describes the high stake decision behind the development of the A380 and how it fared after its launch. It also elaborates the duopoly between Boeing and Airbus, which accounted for 91% of the commercial aircraft market share. The case ends with forward-looking questions on what strategies Airbus can implement after the demise of the A380 to compete with long-standing rival Boeing and new entrants like Chinese aircraft manufacturers in a cut-throat market that was witnessing the commencement of environmentally friendly aircraft projects by the two leading players as the new battlefield.

This case is set in 2020 and talks about a start-up pharmaceutical marketing company - Good Pharma - based in Singapore. One of the first products the firm had embarked on marketing was Suu Balm, a cream for dry and eczema-prone skin, which had been formulated by a lead user - Dr Tey Hong Liang (Dr. Tey) from Singapore's renowned National Skin Centre (NSC). As a lead user innovation, Suu Balm had gone through extensive licensing negotiations before launch and took some time to see market success. The Suu Balm cream was a menthol based formulation to help relieve itch and dry skin conditions. Initially, the cream was sold online and to government and private dermatologists and general practitioners directly. Later the company approached retail pharmacy stores like Guardian and Watsons to distribute the product and saw spiralling sales growth at an average of 180% a year. The firm expanded beyond Singapore to other Asian countries, the U.K. and Ireland, by collaborating with both physical and online retail stores. However, it faced some hiccups in its collaborations with physical stores in Ireland and U.K. and quickly shrank its expansion in these countries after incurring some losses. Dr. Tey had also noted an increasing demand for additional products from his patient visits, which led to the expansion of the Suu Balm brand to include hair care, facial care, and products suitable for children. Effective product and geographical expansion strategies fuelled further business growth, and by 2019, Suu Balm's retail sales had exceeded US$3.69 million in its home market alone. However, Good Pharma wanted to expand beyond collaborations and launch its own products in the market moving forward. Could lead user innovation still be a viable strategy for Good Pharma's next growth stage as a start-up company?