Electives

Shanghai electives

• Investment Banking and Private Equity

  Investment banks and private equity funds are key players in the capital market. This course introduces the history and status quo of investment banks and private equity funds, and the core businesses of these organizations; the equity capital raising, leverage buyout, and M&A with relevant models; and help students understand the basis of decision making in capital raising and M&A via case studies and business simulation.

• Digital Marketing Strategy

  The Internet and digital technologies have continued to alter the way consumers search information, make transactions, and share experiences, as well as the way firms engage with consumers. In today’s digital era, it is imperative for marketers to understand how to gain a competitive edge by leveraging digital media to set targeting strategies and implement the marketing mix. This course will provide a structured framework to introduce students to the most up-to-date tactics, applications, and trends in digital marketing.

  The objective of "Digital Marketing Strategy" course is to discuss and analyze the marketing actions that have been or are being digitized in the process of enterprise marketing—from customer insight to marketing strategy. Based on these analyses, the basic rules, core logic and implementation points of the digital marketing strategy are summarized and compared and integrated with the traditional marketing strategies.

  Students will be familiar with the digital media landscape as it relates to marketing strategy. As digital marketing tactics become more common among organizations, digital strategy will become integrated into the broader marketing strategy. To this end, the course is roughly divided into three main parts:

  (1) understanding online customer journey.

  (2) understanding digital, mobile and social media marketing.

  (3) fusing online and offline marketing strategy.

• Cutting-edge Marketing Research and Analytics

  Ever-changing marketplaces and the related computing environment are making an impact on the structure and content of the marketing manager’s job. Concurrently, marketing is so rapidly evolving that it is no longer based on its conceptual content alone. Even though many still see traditional marketing as an art, the new and emerging marketing increasingly looks like engineering by combining art and science effectively to solve marketing problems. Marketers need more than concepts to fully make use of various and rich data available to them.

  Whether or not you ever work in a marketing research function, at some time in your career, you will most likely need to deal with marketing research, either as a producer or as a user. This course is a concise guide to marketing research as it aims to accomplish the task of integrating theory and analytical practice reasonably well.

  (i) Marketing Research is about providing relevant, accurate and timely information for marketing decisions. This course is designed to provide you with an overview of marketing research and its use in making more effective marketing decisions. Topics covered will be developing research questions and hypotheses; deciding what data to collect, where to collect from and how to collect data; coding and editing of data; using statistical tools to analyze data, interpreting results; and writing and presenting reports.

  (ii) Marketing Analytics is the art and science of developing and utilizing quantitative marketing decision models to plan, implement, and analyze marketing strategies and tactics. This course prepares students for a career in marketing analytics. This involves analyzing data using a set of statistical tools to facilitate good decision-making. The analytic methods are commonly used in e-commerce, grocery stores, retail, utilities and financial industries.

  This is a relatively heavy number oriented course that analyzes data and interprets analysis results. It should be understood that data analyses and result interpretations are two primary ways to understand marketing phenomena and solve marketing problems. This course builds on marketing and statistics courses you have taken. In short, it will give you grounding in what is being called “data-driven marketing.”

• Business analytics and data-driven operation

  The availability of big data spurs data-driven automation of business decision making. When this practice is implemented at the operational level, it leads to data driven operation, also known as machine-learning operations (MLops). Taking the retailing industry as background, this course introduces students to the managerial issues and technical details of business analytics and data-driven operation. The content of the course covers popular machine learning models, sales analytics, assortment analysis, consumer profiling, consumer segmentation analysis, and product recommendation techniques. Students are required to run analytical models on real dataset to produce reports.

• Advanced Business Analytics

  This course mainly introduces the most two important data analysis tools in business analytics: time series analysis and panel data analysis, and their applications.

• Achieving Operational Excellence in Service

  Service operations are an integral part of our daily lives, playing crucial roles in everything from healthcare and transportation to dining, retail, social media, entertainment, and education. We interact with service operations constantly, whether as consumers or providers, filling essential roles for friends, family, and in our professional lives. Given the pervasive and vital nature of these services, it's perplexing that the quality of service we receive is often subpar. Long waits at the doctor's office, repetitive information requests, and delayed deliveries are common frustrations.

  This course explores why such service failures occur and examines the difference between substandard and excellent service delivery. At its core, the quality of service depends on how effectively organizations design, organize, and manage their service delivery operations. Poor service is typically a result of mismanaged organizational resources and a failure to apply essential principles of service operations management. In this course, you will delve into the nature, character, and challenges of managing service operations. We will cover the fundamental principles of service operations management applicable to all types of service organizations. You'll learn to understand, assess, and improve the performance of service operations through detailed coverage of key issues and challenges, along with practical tools and frameworks for managers. As a result, we aim to achieve operational excellence in service. This course presents cases of real-world situations calling for appropriate state-of-the-art models and solution methods for the design, control, and operation of service systems.

• Internet Platform and Ecosystem Strategies in the AI Era

  This course aims to delve into how internet platforms and ecosystems have formed and impacted the current business competitive landscape against the backdrop of the rapid development of AI technology. With the rise of e-commerce, social networks, and various online platforms, corporate competition strategies are undergoing a fundamental transformation.

  This course will analyze the core characteristics of the internet platform economy, such as network effects, platform dynamics, lock-in effects, and the non-scarcity of information products and services, and discuss how to optimize these characteristics through artificial intelligence technology to enhance business competitiveness. The course will particularly emphasize how AI technology empowers internet platforms by improving operational efficiency and user experience through algorithm optimization, data analysis, and automation. We will explore phenomena like the winner-takes-all market, the strategic importance of first-mover advantage, disruptive innovation strategies, and the long tail theory in the context of the internet platform economy. It also covers different product strategies, pricing strategies, marketing strategies, and channel strategies in the new internet economy, analyzing the importance and strategic points of platform-based business model innovation, product development innovation, and pricing model innovation.

  Additionally, the course discusses the strategies and cost-benefit analysis of internet financial platforms, and how businesses can use social networking platforms to build, expand, and maintain customer stickiness and loyalty. This course also analyzes the dynamics of competitive strategies in the current Chinese internet platform economy environment. The course compiles typical teaching cases, the latest industry reports, and the newest research findings and data on AI technology and internet platforms, organizing teaching through case discussions. Each topic is supported by specific corporate and industry cases for students to analyze and explore, thus deepening their understanding of the characteristics of the platform economy and related theories. The course project encourages students to integrate the learned theories with practical business applications, applying the theories to solve practical problems of platform businesses.

• Behavioral Finance

  This course will introduce and explain the evidence of anomalous return behavior found in US equities markets. We will also present some paradigms of stock price movements that are rooted in studies from psychology, and seek to explain trading activity in equity markets. We will begin by exploring some of the evidence that contradicts the standard risk-return paradigm. We will then introduce some of the psychological biases that researchers suspect are inherent to investors. We will then employ some of the results from the psychology literature to explain the irrationalities encountered in the finance literature. Thereafter, we will present the latest evidence on why individual investors trade and how individual and institutional investors form their portfolios. We will also comment on the use of big data to earn abnormal returns vie behavioral finance application.

• Sustainable Finance

  The is designed to provide a comprehensive understanding of sustainable finance principles and practices for master students. The course focuses on the intersection of finance and sustainability, and aims to equip students with the knowledge and skills required to evaluate financial decisions through a sustainability lens.

  The course covers a range of topics, including the role of finance in achieving sustainable development goals, the integration of environmental, social, and governance (ESG) factors in investment decisions, and the evaluation of financial risk and return in sustainable investments. In addition, we will cover a range of topics, including the history and evolution of CSR, the business case for CSR, stakeholder engagement, and the integration of CSR principles into corporate strategy.

  Students will learn about the different types of sustainable finance instruments, including green bonds, social impact bonds, and sustainable investment funds. They will also gain an understanding of the regulatory frameworks that govern sustainable finance, such as the United Nations Principles for Responsible Investment (PRI) and the European Union's Sustainable Finance Action Plan. Students will also learn about the importance of reporting and disclosure in CSR, including sustainability reporting frameworks such as the Global Reporting Initiative (GRI) and the Sustainability Accounting Standards Board (SASB).

  In addition to theoretical concepts, the course will also include practical case studies and examples of sustainable finance in action. Students will have the opportunity to apply their knowledge to real-world scenarios and develop critical thinking skills to analyze and evaluate the impact of financial decisions on sustainability.

• Generative AI for Business: Foundations and Applications

  This course introduces generative AI technologies and their business applications, tailored for international business master’s students. It covers language and image generation tools, with a focus on their use in marketing, management, and decision-making. Through case studies and team projects, students will learn to evaluate and apply GenAI in real-world business contexts.

• Corporate Reporting in China

  This course focuses on corporate reporting of Chinese listed companies. Corporate reports are comprehensive documents submitted by listed companies to securities regulatory authorities and disclosed to the public within specified periods. The course aims to introduce fundamental theories and methodologies of corporate reporting, examine differences between Chinese Accounting Standards and IFRS, and highlight distinctive aspects of corporate reporting with Chinese characteristics.