The marketing doctoral program seeks to prepare students to contribute to the marketing discipline via the discovery, development, and dissemination of knowledge.
The program is designed to equip students with the requisite theoretical background and methodological skills for successful scholarly careers at institutions of higher learning. The marketing group feels strongly that the apprenticeship model is the most efficacious approach to doctoral training and, to that end, students typically engage immediately in research projects with faculty.
Recent students have been successful in publishing these projects in leading journals such as the Journal of Consumer Research, the Journal of Marketing Research, and theJournal of Marketing
Read more about research topics, doctoral student publications, and research awards.
The marketing interest group offers four seminars that provide the theoretical core of marketing doctoral students' training. These seminars introduce the central conceptual and phenomenological aspects of the marketing field, as well as the methodological approaches employed in their examination. Since the field of marketing scholarship segments into consumer behavior, modeling, and marketing management, seminars are offered in each of these areas, plus a methodological and marketing theory seminar.
Beyond these four seminars, students are expected to take an additional four seminars that focus on their chosen area of interest. Students are free to matriculate into courses within the Katz School, other departments at the University of Pittsburgh (such as Psychology, Economics, or Statistics), or at Carnegie Mellon University.
Since strong methodological skills are critical to a successful scholarly career, marketing doctoral students typically take seven or more courses in statistics and econometrics. A minor in analytical methods or advanced statistics is the norm.
A minimum of eight marketing and related courses are necessary to fulfill the requirements of a major in Marketing. In addition, a minimum of four research methodology courses are required from the list below, plus a course in microeconomics, is required.
- Analysis of Variance (PsyEd 2016–Statistical Methods III: Analysis of Variance)
- Probability Theory (Stat 1631: Intermediate Probability)
- Experimental Design (PsyEd 2030: Experimental Design)
- Multivariate Statistics (PsyEd 3416: Applied Multivariate Statistics)
- Multivariate Statistics (Stat 2310: Applied Multivariate analysis)
- Mathematical Statistics (Stat 1632: Intermediate Mathematical Statistics)
- Introduction to Econometric Theory (Heinz 90-906 with Bill Vogt)
[Those with a non-quant background should take 1, 3, 4, and 7; the others are encouraged to take 2, 5, 6 and 7.]
Students typically pursue four courses per semester for two years prior to taking their comprehensive exams in late summer following their second year. The marketing seminars are shown below:
The marketing curriculum leading to the PhD degree is outlined below.
Eight courses in a major, must include:
BMKT 3014 Marketing Strategy
The purpose of this seminar is to give you an overview of the foundations of marketing strategy research and familiarize you with recent marketing strategy research. This seminar examines marketing strategy from a multidisciplinary perspective and utilizes theories emanating from economics, sociology, psychology, management, as well as marketing.
BMKT 3015 Consumer Behavior
This seminar seeks provide students a broad overview of the literature in consumer decision making and behavior. Students will also be encouraged and expected to delve more deeply into areas of their particular interest. Further, students will increase their ability to develop and present their research ideas
BMKT 3017 Marketing Models
This seminar covers quantitative models in the marketing literature, designed for all marketing doctoral students (including those who do not see themselves as quantitative modelers) as well as other doctoral students with an interest in marketing models. The course will provide (a) an overview of the field and (b) in-depth coverage of selected modeling areas. The objective is not merely to inform students about the literature but to develop skills in critically evaluating models and building on current work with original ideas.
BUSADM 3001 Behavioral Research Methods
The primary objective of this course is to familiarize you with and develop an appreciation for business research methodology. Research skills will be an important determinant of your success as an academic. The course will introduce you to a variety of research approaches, allow you to develop an understanding to effectively use these approaches in your own research, and prepare you to evaluate research done by others. The course will also provide you with an introduction to causal modeling techniques (LISREL, PLS). By the end of the course you should develop a sound appreciation of the research process and a range of research approaches that can be applied to management problems. In addition, you should have an appreciation for what constitutes "good" research so that you can constructively critique and make use of research done by others.
BUSADM 3002 Multivariate Analysis in Behavioral Research
This course is intended for students engaging in business research. The course will cover topics such as multiple regression analysis, analysis of experimental data (using ANOVA, ANCOVA, MANOVA, and MANCOVA), logistic regression, and Hierarchical Linear Models (HLM). Emphasis will be placed on analyzing actual data sets using SPSS and HLM software. Students enrolling in this course should already have taken at least one course in basic statistics, and be knowledgeable about bi-variate analysis, hypothesis testing, and basic regression. The course will emphasize replication and extension of previous studies, and writing up research results based on findings from statistical analyses. Learning how to choose appropriate statistical techniques to test hypotheses and how to translate statistical results into written text are key aims of the course.
And four additional courses chosen from the following list and approved by the academic advisor:
- CMU Human Judgment and Decision Making
- CMU Behavioral Economics
- BFAE 3001 Microeconomics
- SPY 2460 Learning and Memory
- CMU Advanced Data Analysis
- CMU Advanced Topics in Emotion and Decision Making
Three courses (minimum) in the minor field of study statistical analysis chosen from the following list and approved by the academic advisor:
- BIOST 2049 Applied Regression
- PSYED 3416 Multivariate Statistics
- BIOST 2063 Bayes and Empirical Bayes Stat
- STAT 625 (CMU) Probability and Math Analysis
- BQOM 3020 Simulation
The purpose of this course is to give an up-to-date treatment of the important aspects of simulation methodology. The topics covered include: modeling and generating stochastic inputs, output data analysis, variance reduction techniques, experimental design and model validation. Application of the simulation techniques in manufacturing, finance, marketing, and other functional areas will be explored. An overview of simulation languages including ARENA will be given.
Students are required to complete an independent research paper and submit it to the marketing faculty in the summer of their first year of study (third term). It is anticipated that this paper will develop into a publishable research article.
Marketing students' dissertations typically consist of three essays addressing an important marketing issue. These essays are subsequently submitted as separate papers to major journals. We have found that this approach is superior to the "magnum opus" dissertation philosophy.