Academic Areas

207. Competing in the Digital Age
Digital technology platforms – smartphones, cloud computing, wired and wireless communications, Internet of Things—have become the foundation for a large share of economic activity, leading to what is called the digital age. Many products have been (music, movies, newspapers, financial instruments) or are being (cars, medical devices, industrial machines) digitized. Marketplaces are increasingly being structured as digital platforms (travel, advertising, auctions). As a result, there is a fundamental and ongoing shift in the sources of value creation and competitive advantage toward digital technologies. We have observed that companies that understand how to harness the power of digital technologies are winning; those that don’t often lose.

Through our research, we have learned that creating value in a technology-driven world is driven by management practices that complement the foundational technologies. A business can succeed by developing new knowhow and business practices suited to the digital age and representing it in software. With better data and advanced analytics, companies can develop a more sophisticated understanding of their customers, operations, and products. 

The objective of this course is to train the next generation of business leaders how to leverage digital technologies to grow their companies profitably. This course will prepare students to drive digital (business) innovation.

We will begin by discussing the technological forces of change. We will then develop the capability to identify emerging technologies that have the potential to disrupt the status quo. We will explain what software is and how it can be leveraged in business. Students will learn the capabilities of new forms of software (like analytics and machine learning) both conceptually and through hands on experience.

We then shift to studying the economics of the digital world, which are different from the economics of a physical world.  Students will learn the economics of digital products and platforms. Based on their understanding of the technologies and their economics, students will then learn how to apply strategy frameworks and gain insights into new ways to compete and organize.

We close with technology decision-making. The objective is for students to develop an understanding of the factors they must consider. These include evaluation of the technology investments from a financial perspective, the timing of the investment, whether to build, buy or partner to acquire the technology, and how to build systems that are adaptive and flexible.

273. Business Intelligence for Analytical Decisions
Digital transformation has enabled the collection of extremely rich and fine-grained data. This course provides an introduction to analytical techniques and frameworks that can be used to solve business problems with the help of data. Topics include clustering for market segmentation, association rules to discover relationships between different purchase decisions, Naive-Bayes classification techniques for decision making, and decision-trees. We discuss how these tools can transform decision making in fields such as operations, marketing and HR.

 275. Advanced Data Analytics (MSBA)
This course covers applications of machine learning methods, such as supervised learning classifiers and unsupervised algorithms, to create computer-based models to understand and analyze text data, e.g., for text categorization, sentiment analysis, clustering documents based on similarity, etc. Students explore these methods on numerous data sets from the industry.

 279. Digital Strategies
This course examines business strategies for firms that make digital products and services. These include computer hardware and software, smartphones and apps, network devices, data analytics, mobile communications, Internet-of-things, and infrastructure such as cloud computing. The insights from this course apply not only to digital firms and industries, but also to other industries that apply their innovations for their own products or services, such as healthcare, banking, biotech, transportation, education, finance, retail, manufacturing, and energy.

The objectives of this course are to help students understand the distinctive features of digital products and services, corporate strategies in those industries, and the broader ecosystems that characterize the industries. By the end of the course, you should be able to (1) understand basic economics of information and networks, (2) apply the concepts of platform competition to digital firms, (3) understand how firms innovate and capture value from innovation in digital industries, (4) apply theories from strategy to digital markets, and (5) understand and explain the relationship of globalization and government policies to digital strategies.

 290. Blockchain and Cryptocurrencies
This course provides introductions to students with an architectural understanding of 'why' and 'how' blockchain was created, what problem it solves, and prior efforts to resolve said problem. Additionally, this course gives students a Bitcoin overview, including history, actors, mechanisms, and issues, as well as an overview of altcoins (e.g., Ethereum). Finally, students will gain an understanding of the challenges and risks involved with this new blockchain technology and cryptocurrency landscape.

 290. Data Architecture
Course description coming soon.

 290. Deep Learning Applications (MSBA)
This course provides students the fundamentals of deep learning which is driving many business applications in image recognition, natural language understanding, language translation, and conversations. Also, it introduces students to Keras and TensorFlow for designing their deep learning projects and many approaches to deep learning – ANN, CNN, and RNN.

The course is designed at four levels of depth. The first level introduces students to deep learning as end-user in our day-to-day activities. At this level, students understand how the performance of these models is measured and how they are deployed. The second level explores how a pre-built deep learning model can be customized. At this level, students focus on customization tooling and supervision options. The third level expands on how students can build a deep-learning model from scratch using standard components. This level exposes students to additional capabilities, such as hyper-parameters and how they can be tuned. Finally, the fourth level shows students how researchers are developing new deep-learning models using mathematical and statistical tooling, and exposes to some advanced topic in early research.

 290. Python for Management
Course description coming soon.

 290. Software Thinking for Managers
As businesses increasingly operate like tech companies, future executives must possess an understanding of the role and impact of software in business: what software makes possible, what problems it can solve, and how software technologies will advance in the future. To achieve this goal, this class will discuss key developments and advances in software technologies, highlight how the different components of software (ranging from those that interact closely with the machine to those that interact with users) work together, teach systems thinking and algorithmic approaches to problem solving, and provide introductory programming skills.

 290. Technologies & Analytics Consulting (MSBA)
Digital customer channels are maturing in providing personalized customer-facing functions, such as advertising, sales, ordering, and product use. Social engagement is now a predominant way for influencing customers and creating buzz. Cognitive techniques are providing a more human touch, even when dealing with software agents. The success of new customer engagement is heavily due to advanced analytics capabilities to drive personalized communication to each customer or micro segment. There is a tremendous need in organizations to establish programs for analytics-driven customer engagement. In this course, students learn elements of analytics and personalized engagement. Students will also work on a project using real-life business problem and data to get hands on understanding.

290. Data and Program Analytics
The volume of data being generated every day continues to grow exponentially. We capture and store data about pretty much every aspect of our lives. Being able to handle and analyze the available data is now a fundamental skill for everyone. The objective of this course is to challenge and teach students how to handle data that come in a variety of forms and sizes. This course guides students through the whole data management process, from initial data acquisition to final data analysis. Topics that may be covered, include: regular expressions, accessing data sources, relational databases and SQL, data cleaning, processing and manipulation using Pandas, basic statistical inference models, principles in random experiment design, basic predictive modeling techniques, textual data and natural language

 294. Big Data Analytics with Hadoop (MSBA)
This course offers an in-depth hands-on exploration of various cutting-edge information technologies used for big data analytics. The first half of the course focuses on using Hadoop – Sqoop, Pig, and Hive - for ETL (extract-transform-load) operations. The second half of the course focuses on understanding the MapReduce algorithm and using Apache Mahout for data mining algorithms, including classification, clustering, and collaborative filtering. Towards the end of the course, students will be introduced to Apache Spark. Students will become familiar with the Unix operating system, as well as with programming in Hadoop and Scala. This course is extremely hands-on as students will spend significant time working with data. Students are expected to have taken at least one course in data modeling and one course in data mining (see prerequisites) or have significant related work experience.

 294. EDGE
Edge is Merage’s MBA integrative course that explores the crucial roles of global, market, and technology forces in the business landscape as disruptive and transformative catalysts for change - opening new markets, erasing boundaries, and reinventing industries. In a world that is being redefined by these catalysts - an evolving geopolitical order, a demand for sustainability, shifting demographics, changing consumer preferences, digital technologies, ongoing economic uncertainty, and relentless competitive pressures- the imperative for companies to pursue business reinvention and new leadership strategies is unprecedented. This course will prepare future business leaders to proactively identify the opportunities and challenges presented by these catalysts, provide valuable frameworks to critically evaluate their implications, and develop the key strategies, insights, and approaches needed to innovate, compete and win at the Edge.

 295. Big Data Management Systems (MSBA)
The course will cover relational and non-relational databases, cloud data management solutions, as well as the underlying storage and security properties of these systems. Students will broadly study big-data management frameworks such as Hadoop and Spark and also participate in a hands-on project to conduct data analytics, based on real data, drawn from public sources such as the web or social networks.

 Digital Strategy Electives

291-IS1. Governance, Management and Impact of IT (2 units)
IT has become a critical driver of growth in companies and economies, accounting for 50% of capital investment in the US. Accordingly, understanding the drivers and impacts of IT investment is a major area of research in information systems. Initially, research was unable to empirically associate positive outcomes to IT investment, however, more recently, research at the firm and country levels has shown that IT investments contribute strongly to output growth, productivity and market value. These findings reflecting excessively high returns on IT investment presents a puzzle that is the subject of current research. The potential for such high returns also points to the importance of studying effective management of IT. This seminar will cover topics such as contribution of IT investment to firm-level and country level productivity; role of IT in multifactor productivity growth; role of IT in globalization; incorporation of IT risk and externalities; and impact of unmeasured investments in organizational capital and intangible assets. We will also cover topics on IT governance such as the role of contract design in achieving effective governance of IT sourcing relationships; economic impact of IT outsourcing focusing on market returns and on labor productivity; pricing of IT products and services; and HR practices and human capital development policies that affect information workers’ performance in unstable environments characterized by offshoring.

291-IS2. Digital Business (2 units)
Businesses will succeed in the global innovation economy by deriving competitive advantage from IT-enabled strategies and business models. Innovation in organization structure and in processes is a critical component of innovation, and one that is less easily replicated than product innovation. This seminar will study the role of IT in business innovation including business model innovation, and digital business strategies. Business model innovation includes research on network enabled firms and the location of work. Digital business strategies include leveraging customer information for business intelligence and personalization; personalization-for-privacy tradeoffs; design and pricing strategies for electronic marketplaces; role of reputation systems and transaction costs in consumer-oriented electronic markets; analysis of IT-enabled social networks; impact of social media on organizations and markets; supply chain strategy for digital goods; and pricing and versioning strategy for information goods.

291-IS3. Economic Theory in IS (2 units)
Technology is changing rapidly and enabling many new ways of doing business. This rapid pace of change makes it important to identify underlying principles and frameworks that can help explain emerging phenomenon. Economics provides a number of such frameworks and this course will cover such topics including transaction cost economics and search costs; agency theory; theory of network goods; systems competition; compatibility decisions and the role of standards; complementary products; auction theory; price discrimination and product versioning; horizontal and vertical differentiation models; Information goods; product bundling and competition; and applications of economic theory in electronic markets and electronic commerce.

291-IS4. Pricing Strategies for Information Goods (2 units)
This course will introduce the classic Principle-Agent models, and discuss how these models can be applied to Information Systems economics research. The course consists of lectures on the basic models and in-class presentations and discussions on selected articles.