A Ph.D. in marketing at the David Eccles School of Business trains students for careers in scholarly research. The PhD program is rigorous and demands total dedication. This implies preparation and participation in coursework as well as active participation in research. Our faculty invests heavily in training and working one-on-one with doctoral students to teach them how to think about and do research. The Ph.D. qualifying exam in the form of first and second-year papers helps students get involved in the research process from very early in the program. Marketing Ph.D. Coordinator: Promothesh Chatterjee

Three Areas of Study

The Marketing specialization offers three specific areas of study.  A student can pursue quantitative/managerial marketing, computational marketing, or consumer behavior areas of emphasis while completing a Marketing Ph.D.

Quantitative and Managerial Marketing

The quantitative marketing faculty study theoretically grounded empirical analysis of applied marketing problems. This line of inquiry draws primarily on fundamentals in applied microeconomic theory, industrial organization, econometrics, and statistics. The primary research orientation of most faculty members in this area revolves around making rigorous conceptual and theoretical advances and empirically testing theories in the strategy area.

Questions of interest include investigating consumer choices and purchase behavior, new product development, channel issues, and analysis of competition in a wide range of domains. A common theme of research is the use of rigorous quantitative methods to study important, managerially relevant marketing questions.

Computational Marketing

Faculty in this area utilize Machine Learning algorithms to develop strategies that can inform both consumers and firms in the marketplace. This area of specialization draws from computer science, linguistics, and mathematics to test marketing theories as well as apply algorithms to improve marketplace decisions.

Faculty apply a variety of cutting-edge methods to analyze structured as well as unstructured data (such as text, image, and video). The methods range from deep learning, natural language processing, neural nets, adversarial networks, image and video analysis applied to gathering insights about consumer decision-making, product development, marketplace predictions, and ethical decision-making.

Consumer Behavior Marketing

The faculty pursuing consumer behavior marketing study how individuals behave in consumer-relevant domains. This area of marketing draws from social psychology and behavioral decision theory that includes a wide variety of topics such as judgment and decision making, social influence, motivation, cognition, and emotions.

To facilitate research in this area the Marketing Department maintains a participant pool for data collection along with a behavioral and computer lab. Faculty use a variety of methods including surveys, lab experiments, and field studies to test marketing theories and marketplace applications.

Typical Program of Study

Each student’s program of study is tailored to the student’s needs and interests. Students work with their department Ph.D. Committee or Supervisory Committee Chair to design their program of study.
Below is an illustrative list of classes that might be used to compose a program of study.

A minimum of 15 major field, 9 allied field, and 15 research competency credit hours are required. Three credit hours in research must be a Philosophy of Science course. Students are also required to take an effective teaching course. Once students have completed all the necessary requirements to advance to candidacy, they are then required to complete a minimum of 14 hours of thesis research.

To learn more about each course, read the course descriptions in the General Catalog and Class Schedules.

“Working with PhD students is one of the most rewarding aspects of my academic career! I  look forward to the many fruitful research discussions that result in eventual journal publications.”
— Professor Himanshu Mishra

  • MKTG 7700: Strategic Marketing
  • MKTG 7880: Machine Learning for Business Research
  • MKTG 7740: Marketing Models I
  • MKTG 7800: Seminar on Consumer Judgment and Decision Making
  • MKTG 7810: Consumer Behavior Research in Marketing
  • CS 6190: Probabilistic Modeling
  • CS 6340: Natural Language Processing
  • BME 6500: Mathematics of Imaging
  • CS 6955: Deep Learning
  • CS 6969: Ethics i