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Ph.D. in Marketing

Graduate Program - Business Students
Full-time Program

Coursework

Major Courses

MKTG 901: Research Methods in Marketing

MKTG 951: Consumer Behavior

MKTG 952: Introduction to Marketing Models

MKTG 957: Managerial Issues in Marketing

DSCI 920: Probability for Business Research

Foundation: Consumer Behavior Track Courses

BE 917: Advanced Managerial Econ OR ECON 700: Survey of Microeconomics OR Equivalent Course

Supporting: Consumer Behavior Track Courses

Choose at least three of the following courses, with advisor's approval

Courses outside the list below may also be considered, with advisor's approval.

PSYC 578: Social Attitudes

PSYC 723: Advanced Cognitive Psychology

PSYC 725: Cognitive Neuroscience

PSYC 735: Psycholinguistics I

PSYC 774: Advanced Social Psychology I

PSYC 775: Advanced Social Psychology II

PSYC 784: Proseminar in Communication and Aging

PSYC 787: Multidisciplinary Perspectives on Gerontology and Aging

PSYC 831: Advanced Human Learning and Memory

PSYC 885: Altruism and Helping Behavior

Methods: Consumer Behavior Track Courses

Choose at least three of the following courses, with advisor's approval

Courses outside the list below may also be considered, with advisor's approval.

PSYC 791: Statistical Methods in Psychology II

PSYC 818: Experimental Research Methods in Social Psychology

PSYC 893: Multivariate Analysis

PSYC 894: Multilevel Modeling

PSYC 895: Categorical Data Analysis

PSYC 896: Structural Equation Modeling I

PSYC 933: Seminar: The Measurement of Attitudes

PSYC 983: Methods & Professional Issues in the Cognitive & Brain Sciences

PSYC 991: Longitudinal Data Analysis

PSYC 993: Seminar:

PSYC 996: Structural Equation Modeling II

DSCI 921: Statistics for Business Research

Three additional courses with advisor's approval

Foundation: Quantitative Track Courses

DSCI 921: Statistics for Bus. Res. OR MATH 728: Statistical Theory

DSCI 922: Advanced Regression

ECON 817: Econometrics I

ECON 818: Econometrics II

Supporting: Quantitative Track Courses

BE 917: Advanced Managerial Econ OR ECON 730: Topics in Industrial Org

ECON 800: Optimization Techniques I

ECON 801: Microeconomics I

ECON 809: Optimization Techniques II

ECON 916: Advanced Econometrics II

EPSY 941: Bayesian Statistics

EECS 649: Introduction to Artificial Intelligence

EECS 738: Machine Learning

EECS 837: Data Mining

EECS 839: Mining Special Data

Requirements

Area of Concentration

Each aspirant, with the assistance of his or her faculty advisor and the area faculty, selects an area of concentration. The area of concentration is selected from the traditional business disciplines of accounting, finance, human resource management, marketing, decision sciences, organizational behavior, and strategic management. An aspirant may also propose an interdisciplinary area of concentration that is a combination of these disciplines or include emphasis such as international business, law, and economics. The aspirant must take at least five advanced courses in the area of concentration. These courses may include those offered outside the School of Business.

Supporting Areas

Coursework in the area of concentration is supplemented and strengthened by study in one or two supporting areas. A supporting area is one that supplements and complements the area of concentration. The aspirant will satisfy the supporting area requirement by taking at least four advanced courses in the supporting areas (at least two courses in each of two supporting areas, or at least four courses in one supporting area). Courses recommended for preparation for the qualifiers may not be included in satisfying the supporting area requirement.

Research Methodology

For successful qualifier assessment, the student’s program of study should include adequate preparation in research methodology. A sound research is always grounded on sound methodology. A doctoral student in marketing has the opportunity to develop methodological skill in probability and statistics, optimization, uncertain reasoning, game theory, and econometrics. A typical doctoral dissertation often utilizes one or more of the following research methodology: empirical, analytical, behavioral, and computational.

Timeline

Year 1

Coursework and research

Year 2

Coursework and research

Year 3

Comprehensive exams

Year 4

Dissertation proposal

Year 5

Dissertation defense

Some students can complete the program in four years.

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