GCOM 7140 is a research-oriented class that examines how firms can leverage customer analytics to successfully create, manage, and grow brands. The class provides marketing managers and operational business leaders with the analytical tools to develop and operationally execute brand strategies that enhance customer engagement and loyalty.

Consumer Behavior and Pricing Strategy integrates our understanding of consumers from research in marketing, psychology, and behavioral economics. We will take the perspective of a marketing manager and employ this knowledge to develop, execute, and implement effective marketing strategies. Prerequisite: M.S. in Commerce students only

This course will expose you to the knowledge and skills required of, 1) brand managers as they successfully launch and manage branded products/services over time, and 2) brand consultants who consult brand managers on the best strategies and techniques for managing brands. You will also learn the process for conducting a brand audit through a group semester project.

Examines ways to design, develop and execute effective integrated, web, and social marketing programs. The course uses a business planning model which allows students to justify, build, and execute social and digital marketing programs with bottom line ROI. Students learn to identify and measure high value market segments, use web and social research to evaluate competitors and convince management of the value of digital and social marketing.

Through labs, assignments, and a capstone project, students build, evaluate, & deploy predictive ML/AI models using low-code technologies and learn how to apply these concepts to create value & support real-world applications. Students will also learn managerial considerations employing analytics initiatives to create business & societal value. No prior experience with coding, machine learning, or AI is assumed or expected.

This course aims to provide students with a practical understanding of Artificial Intelligence technology. It covers key factors for the successful development, deployment, and management of AI, machine learning, and other algorithmic approaches to automated decision-making. Students will better understand the societal impacts of AI, ethical considerations in the use of AI, the limitations of AI, and approaches to balance AI risks and benefits.

The course provides an overview of the fundamentals necessary to conduct data analytics with Python including understanding Python objects, data types, structures, packages, and data flow statements; and, reading, writing, manipulating, and plotting data. Students will perform predictive analytics via machine learning using industry-standard packages.

Students will learn how to communicate effectively with data and data structures. This includes how to evaluate potential sources of data, aggregate data values from multiple sources, and compile creative, professional, and descriptive visualizations from that data. Students will learn the best type of chart or figure for different situations and how to format those visualizations to maximize the impact to the viewer.

Multivariate statistics training to analyze Big Data sets. The course covers discrete choice modeling (logistic and probit models), classification techniques (discriminant and cluster analyses), data reduction techniques (factor analysis), and advanced predictive techniques (regression models with interactions and curvilinear effects, structural equation modeling, and factorial ANOVA). Trains students on IBM-SPSS, SAS, and R.

This course provides students with an introduction in how to effectively fill the role of Project Manager. It covers a blend of conceptual knowledge and practical skills necessary for the effective management of complex projects.

This course is designed to provide a broad overview of management consulting and other related advisory services professions while also helping students develop skills that are broadly applicable in these professions as well as in other fields (business, politics, not-for-profit, etc.). Working both individually and in teams, students will gain an appreciation of what makes consulting and advisory services unique from other areas of business.

This course is focused on harnessing the power of unstructured data to perform advanced analytical techniques. Students will be exposed to big data technologies (NoSQL, Hadoop, etc.) to understand how to manage and interact with large, complex data sets. We will also cover various analytical and machine learning techniques that can apply to these data, with particular attention to text data from reports, articles, and social media.

This course is second in a two-seminar sequence that introduces students to the science and business of the biotechnology industry. In addition to continued exploration of translational research, this course will focus on deeper scientific and commercialization topics specific to the industry, including operational and financial perspectives across all stages of organizational maturity. Students will learn from industry leaders who are commercializing, analyzing, and investing in biotechnology.

This course focuses on how to successfully commercialize breakthrough technologies that have high potential to generate social and/or economic value. Issues related to identifying market needs and potential, developing commercialization plans, and understanding business models and entrepreneurial strategy are covered. As an introduction, this is not an appropriate course for students who minored in or have a strong foundation in entrepreneurship.

This course is designed to expand your knowledge of financial reporting from a user's perspective. To do this, we use firm disclosures to explore: how analysts use financial information to value the firm, how some managers attempt to alter perceptions of firm value, and how accounting rules can impact perceptions of firm value. Restricted to MS in Accounting Students.

This course helps students understand how behavior, psychology and biases influence the preparation, interpretation, and auditing of accounting information. The class will explore theories and research on judgment and decision making, and how those theories apply to aspects of financial reporting and auditing. Restricted to MS in Accounting Students.

Includes the planning, processes (gathering evidence), & judgments required to render an opinion on an entity's internal controls and financial statements. Deals with evidence theory, risk identification & professional judgment. Audit methodology is examined through a study of auditing standards & the concepts & procedures developed to implement those standards. Other topics include data analytics, auditor independence, materiality & audit reports.

Given the widespread use of financial reporting and the growing use of Big Data, business institutions have increasing demand for people who can bridge the disciplines of data, analytics methods, and decision making. This course is designed to develop your ability to extract, analyze, and interpret information from required financial reporting.

The course addresses the various business, tax, and accounting issues arising in connection with the formation, operation, and termination of domestic corporations and their shareholders. It provides in-depth coverage of the technical rules of Subchapter C, and places special emphasis on the identification and implementation of tax planning strategies available to corporations and their shareholders. Restricted to MS in Accounting Students.

Today's CPA must have a working familiarity with a number of areas of business law to properly advise clients and to protect their own interests as a practitioner. This course is designed to meet both objectives. The course is broken into six main parts: (1) business entities; (2) civil liability and unfair competition in business; (3) intellectual property; (4) employment law; (5) contracts; and (6) bankruptcy law for businesses.

Presents the opportunity to examine new and emerging IT topics or study a particular IT related area in greater depth than is covered in other courses. Prerequisite: Graduate Commerce.

This course will focus on global, environmental, and social sustainability and resilience. We will explore how corporations and non-governmental organizations can address and impact change in our current environment. We will study successful leadership strategies within corporations and by social entrepreneurs in effecting societal changes.

Teaches analytical consulting competencies focused on the fast-paced financial industry: 1) Process automation: automating repetitive tasks to increase individual productivity; 2) Financial business intelligence: accessing and manipulating information stored in organizational databases; 3) Financial Engineering: designing and implementing financial algorithms that make financial decisions. More at: http://webs.comm.virginia.edu/Grazioli/GComm7720

This course familiarizes students with the restructuring of financially distressed firms and distressed investing. We analyze credit documents, model credit risk, and survey restructuring methods. Throughout, we consider credit and distressed debt as asset classes and develop techniques and models for investing in credit and distressed instruments.

GCOM 7730 explores three main topics: (1) mergers and acquisitions (2) non-distressed corporate restructurings in the form of leveraged buyouts and private equity and (3) distressed corporate restructuring/bankruptcy. The course is largely case-based and extends concepts and principles learned in GCOM 7060 and GCOM 7710 to practical applications. Students will additionally participate in two negotiation exercises during the term.

This course develops the concepts and tools needed to build and analyze investment portfolios for a wide range of investors including sovereign wealth funds (SWFs), pensions, endowments, family funds, high-net worth individuals, and even small investors taking into account a broad array of investing objectives. The course covers risk/return trade-offs and valuation in the equity, fixed income and derivative markets.

Develops an analytical framework by which individuals and institutions can make real estate investment and financing decisions. Emphasizes theory, concept building, financial modeling, and practical real estate applications. Uses the case method to illustrate implementation of an analytical framework. Restricted to Graduate Commerce.

This class provides students with a deep understanding and hands-on experience with information technology in business settings: advanced Excel features, macros, pivot tables, SQL, databases. By the end of the class students will have developed and tested an Excel-based system to solve a complex business problem in a financial setting. More at http://webs.comm.virginia.edu/Grazioli/GCom7770 Restricted to MS Accounting students.

This interdisciplinary course explores four critical areas at the intersection of business and sustainability: 1) Climate Finance, 2) Conservation Finance, 3) Circular Economy and 4) ESG Investing. In addition to acquiring an understanding of these key sustainability challenges, participants will gain skill in applying analytical tools and techniques to the evaluation of sustainable investment opportunities.

The primary objective of this course is to provide a blend of theoretical knowledge and practical skills necessary for the effective management of IT products. To this end, the course consists of seminars, workshops, and tutorials on contemporary tools and techniques. Students apply the concepts and tools covered in class by completing a set of individual assignments and by working as a team to conduct a product design sprint.

"This course teaches the ""why"", the ""what"", and the ""how"" of digital transformation from the perspective of incumbent firms that are reinventing themselves to compete in the digital era. Students will learn about consumerization, democratization, datafication ad platformization, and how to drive a digital transformation journey. Teams of students will apply these ideas to a specific organization and help them plan their digital transformation."

In this course, students will survey digital technologies that are changing products and services and the way we make decisions and run business operations. While specific topics vary from year to year, examples include new ways to manage data, business intelligence, AI, business analytics, multi-sided digital platforms, the Internet of Things, and the blockchain.

This course exposes students to the international issues, business practices, and concerns in their respective global immersion location. Prerequisite: Restricted to MS in Commerce students.

Students taking this course will explore areas and issues of special interest that are not otherwise covered in the graduate curriculum. This course is offered at the discretion of the supervising professor.