BDBA - Doctor of Business Administration

BDBA750 Customer Analysis (3 Credits)

Focuses on the analysis of customer decision-making and how marketing strategy can be used to influence those decisions. The framework used is the buyer behavior model, in which concepts from psychology, sociology, and economics are applied to individual and organizational purchase decisions. Marketing strategies of leading firms in consumer products, technology, and services (including internet services) are analyzed using a variety of case study formats.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA752 Marketing Research and Analytics (3 Credits)

Provides a review of primary data collection methods for marketing data. Students will learn how to design and implement effective confirmatory research. Both direct methods such as surveys and indirect methods such as experiments will be covered. In this hands-on course, students will design and conduct research with target customers, analyze the data, and then present their results to decision makers.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA802 Data Mining and Predictive Analytics (3 Credits)

An introduction to the essential tools and techniques of data mining/machine learning. Students will learn (1) how to execute the key steps in the data mining process - including data preprocessing, data exploration and visualization, supervised and unsupervised learning, model selection and validation, and complexity control; and (2) how to build reliable predictive models. The data mining methods covered are Linear Regression, Logistic Regression, K-nearest neighbors, Classification and Regression Trees, Ensemble methods, K-Means and Hierarchical Clustering, and Association Rules. The focus will be on business applications - realistic data from Marketing, Finance, Operations, and other functional areas will be used to illustrate the breadth of applications.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA804 Big Data and AI for Business (3 Credits)

Big data offers immense potential for insights and wealth creation, generating vast data volumes. This data is often unstructured and real-time, challenging traditional data management and presenting both challenges and opportunities. Advanced techniques, especially AI, are essential for harnessing data value. This course emphasizes hands-on learning about Big Data and AI, including strategic implications and technological underpinnings with tools like deep learning and AWS. Through practical examples and assignments, it aims to build familiarity with these technologies and foster strategic business thinking. The evolving tech landscape necessitates a flexible learning approach, ensuring manageable student workloads.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA806 Executive Decision Making in the Age of AI (3 Credits)

Artificial Intelligence (AI), in an unprecedented and transformational manner, has recently opened up new possibilities for firms that significantly affect how humans aided with technology make decisions. This course will focus on understanding AI capabilities (including predictive and generative models), designing effective decision-making frameworks that incorporate AI and humans, building a deep appreciation and understanding of some key issues surrounding AI in organizations, and helping develop governance structures for AI in organizations.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA807 Theoretical Foundations of Digital Organizations (3 Credits)

Introduces students to scientific paradigms and research perspectives relating to the changes brought about by digitization and digital technologies. Digital technologies have fundamentally transformed businesses, markets, and societies. Businesses that build on emerging digital and information technologies have several unique and interesting characteristics that set them apart from traditional businesses. Examining the fundamental characteristics of these digital businesses, platforms and ecosystems will help us understand the transformative potential of digital technologies and their impacts on the structure and competitive dynamics in various sectors. This course is designed to foster an in-depth understanding of fundamental concepts relating to the digital economy and will explore a series of research questions about the consequences of these developments for consumers, organizations, and society at large.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA808 Special Topics in Information Systems (1-4 Credits)

Special topics specific to the Information Systems doctoral field of study.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of BMGT-Robert H. Smith School of Business.

Repeatable to: 18 credits if content differs.

BDBA818 Special Topics in Accounting (1-4 Credits)

Special topics specific to the Accounting doctoral field of study.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

Repeatable to: 18 credits if content differs.

BDBA820 Economics for Business Research (3 Credits)

Investigating the implications of the major findings of behavioral economics for policymakers. Analysis of the ways in which individuals make decisions that systematically depart from the standard model, which assumes perfect rationality, perfect selfishness, and perfect willpower. Students will develop an understanding of how models are constructed, and how this forms the basis for empirical estimation strategies. We first discuss concepts such as endowment effect, loss aversion, and status-quo bias. Then we introduce uncertainty. The standard model of decision-making under uncertainty is the expected utility model. We then go on to describe some empirical evidence from both economics and psychology to illustrate violations of the expected utility model. Next, we will discuss intertemporal choice. After introducing the standard model of discounting, we will again discuss some observed violations of the standard model in the data.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA822 Quantitative Research Methods (3 Credits)

This is a course in basic statistics. Statistical methodologies are increasingly used in various disciplines, e.g., data science, applied statistics, business, and computational social science. The main goal of this course is to provide students with an introduction to different types of quantitative research methods and statistical techniques. This course primarily covers two components: 1) methods for quantitative research, and 2) quantitative statistical methods for data analysis. With these, we hope you will obtain knowledge necessary to do high quality scholarly research and more efficient and effective practice in your daily tasks. In particular, it involves learning statistical inference under which you should be able to digest publications about new methods, implement these methods, apply them to your data, interpret results, and explain them to others. In addition, we also expect you to know how to write and publish your novel work in some journals.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

BDBA848 Special Topics in Finance (1-4 Credits)

Special topics specific to the Finance doctoral field of study.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of the Robert H. Smith School of Business.

Repeatable to: 18 credits if content differs.

BDBA858 Special Topics in Marketing (1-4 Credits)

Special topics specific to the Marketing doctoral field of study.

Restriction: Must be in Doctor of Business Administration (BDBA) program; or permission of BMGT-Robert H. Smith School of Business.

Repeatable to: 18 credits if content differs.