Understanding human behavior in organizations and solving problems requires the integration of a variety of social science and related disciplines. A distinguishing feature of the Tepper School's OBT Ph.D. program is the broad interdisciplinary training it provides across an array of areas (e.g., psychology, sociology, economics, strategy, and computer and data science). Not only do OBT doctoral students interact with other students and faculty within the Tepper School of Business, through cross-registration in courses and participation in colloquia, OBT doctoral students also have opportunities to interact with students and faculty in departments such as Engineering and Public Policy, Human-Computer Interaction, Social and Decision Sciences, Psychology and a variety of departments at the University of Pittsburgh. A cornerstone of the OBT Ph.D. program is its methodological training and rigor. From computer science courses in machine learning and AI to courses in advanced statistical methods, students develop a deep understanding of analytical methods and tools.

Collaborative Culture

A small number of students are accepted into the group each year, with a total of about 10 OBT doctoral students in residence. Student-faculty relationships are close, which permits the tailoring of the program of study to fit the background and career goals of the individual.

Course of Study

Our program emphasizes preparation for careers in scholarly research, and graduates of the program usually pursue careers in academic or research institutions. During their course of study, students have the opportunity to engage with faculty in doctoral seminars and joint research, meet with visiting scholars, and interact with other faculty and students across campus. We prepare our graduates to be competitive on the academic job market by getting them involved in research from Day 1.  Program requirements include the successful completion of two research-based papers in the first and second years of the program, qualifying exams, a “minor” area requirement and a doctoral dissertation.  

Research Specializations

Diversity, Inclusion, and Human Capital

Diversity is at the core of many important organizational problems and many of our OBT faculty make important contributions to the growing knowledge base on diversity and its impact on individual, group, and organizational outcomes.

Faculty Research Interests

• Rosalind Chow: gender and promotion processes
• Oliver Hahl: gender, race, and cultural capital effects on supply and demand for human capital in markets (i.e., hiring and career outcomes)
• Denise Rousseau: the employment relationship, evidence-based management
• Catherine Shea: gender issues in management, advice seeking, interpersonal dynamics
• Laurie Weingart: gender and non-promotable tasks in the workplace, gender and negotiation, interdisciplinary teams
• Anita Williams Woolley: gender diversity, cognitive diversity and team collective intelligence

Ethics and Justice

Unethical and unjust behaviors are costly to organizations and society. The OBT group in the Tepper School has three members with expertise in the areas of business ethics and social justice (Aven, Chow, and Cohen). The Tepper School is also home to ethics scholar Tae Wan Kim, whose research takes philosophical perspectives on business ethics.

Faculty Research Interests 

• Brandy Aven: relational attributes of fraud and corruption
• Rosalind Chow: perceptions of and responses to social inequality
• Taya Cohen: interpersonal misconduct, workplace deviance, moral character, guilt, shame, trust and trustworthiness
• Tae Wan Kim: artificial Intelligence ethics, future of work, business ethics

Groups and Teams

The OBT group in the Tepper School houses three scholars who are leaders in the areas of groups and teams (Argote, Weingart, and Woolley) and others whose work is directly relevant (Aven, Chow, Cohen, and Hahl). The Tepper School and Carnegie Mellon more broadly host several other faculty who work in this area (Carley, Kiesler, and Krackhardt). We regularly graduate students who conduct research on groups and teams.

Faculty Research Interests 

• Linda Argote: learning, transactive memory and knowledge transfer within and between groups
• Brandy Aven: networked teams
• Rosalind Chow: power and status within/between groups, impacts of diversity on group functioning and performance
• Taya Cohen: cooperation and conflict within and between groups, pathways to status and leadership in groups
• Oliver Hahl: perceptions of status, authenticity and identity within/between groups
• Laurie Weingart: conflict in teams, multiparty negotiation, negotiation and group dynamics
• Anita Woolley: collective intelligence, team strategic orientation, team performance

Knowledge Transfer and Learning in a Technologically-Driven World

The OBT group in the Tepper School includes scholars whose work has been foundational to the field of organizational learning (Argote) and includes four other scholars who are substantially engaged in the growing body of work on knowledge transfer and learning (Aven, Hahl, Lee, and Woolley). Reflecting the Tepper School's focus on the intersection of business and technology, faculty research involves responses to rapid change, coordination of work distributed across time and place, organizational learning. Our work also connects to scholars working in related areas in Information Systems (Mukhopadhyay and Singh) and Economics (Epple) at the Tepper School, as well as researchers at Heinz (Krishnan), Engineering (Fuchs), and Computer Science (Carley, Dabbish, and Rose) at Carnegie Mellon, also conduct research relevant to learning.

Faculty Research Interests 

• Linda Argote: transactive memory systems, knowledge transfer, organizational learning, the effects of technology on learning and knowledge transfer
• Brandy Aven: transactive memory systems, the effects of technology on networked systems for learning and knowledge transfer
• Oliver Hahl: learning and knowledge transfer, effect on firm performance
• Sunkee Lee: organizational learning, effect of the spatial design of workplaces and incentive systems on organizational learning, knowledge transfer, exploration vs. exploitation, learning from own and others’ experiences
• Anita Woolley: learning and collective intelligence in groups and organizations, increasing collective intelligence in human-computer systems

Networks and Organizations

Research on the formation and consequences of social networks in organizations and markets have become central to our understanding of how organizations and markets work. The OBT group in the Tepper School hosts four scholars who work on important areas related to the role of social networks in organizations (Argote, Aven, Hahl, and Shea). Researchers at Heinz (Krackhardt) and Computer Science (Carley) at Carnegie Mellon, also conduct research in areas that inform our knowledge of social networks as well as the methodologies employed to distinguish their antecedents and effects.

Faculty Research Interests 

• Linda Argote: learning and knowledge transfer through social networks
• Brandy Aven: formation of social networks, persistence (or not) of social networks, learning and deviance within social networks, knowledge sharing in social networks
• Oliver Hahl: identity in social networks, perceptions of brokers in networks, organizational networks and individual performance
• David Krackhardt: social network analysis theories and methods, informal organizations
• Catherine Shea: social network cognition, network formation, experimental methods in social networks

Entrepreneurial and Organizational Strategy

The “Carnegie School” has long influenced research on strategy, particularly by looking at the microfoundations of strategic selection, implementation, and performance. The OBT group in the Tepper School hosts four scholars who work on important areas in firm strategy (Argote, Aven, Hahl, and Lee) that all tie back to the Carnegie School’s foundations in the Behavioral Theory of the Firm. Additionally, scholars in Economics and Marketing (Miller, Epple and Derdenger) at the Tepper School and in the Engineering and Public Policy school at Carnegie Mellon (Fuchs and Armanios) also collaborate in research with Tepper faculty and students research in areas that inform organizational theory, entrepreneurial strategy, firm strategy selection and implementation, and firm performance.

Faculty Research Interests 

• Linda Argote: organizational learning and capability development, micro foundations of strategy and firm performance, behavioral theories of strategy
• Brandy Aven: entrepreneurial strategies, entrepreneurial teams, behavioral theories of entrepreneurship and strategy
• Oliver Hahl: identity-based strategies, categories, diversification, status and authenticity in markets, human capital management and firm performance, microfoundations of strategy and firm performance, behavioral theories of strategy
• Sunkee Lee: organization design, exploration/exploitation, incentives, spatial design, response to performance feedback, firm acquisition behavior and performance, microfoundations of strategy and firm performance, behavioral theories of strategy

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates.

Requirements

The Organizational Behavior and Theory (OBT) doctoral program has two components. Students take courses in each of them. The qualifiers are organized around these two components as well. The two components are:

1. Micro Organizational Behavior Theory and Methods
2. Macro Organizational Behavior Theory and Methods

Current Recommended Courses

All courses are at the Tepper School unless otherwise noted.

Three courses are highlighted as Year One. These are the three courses that are the core courses for the qualifier. All students should take these courses.

Students, with the advice of their advisor, should choose micro, macro, and methods classes suited to their needs. The Tepper School graduate seminars are taught by the OBT faculty at the school.

In addition, we offer three different seminars in topical areas in OBT. These will vary from year to year. They are labeled as topical seminars.

Micro Organizational Behavior and Theory

• Seminar in Organizational Behavior (Core Course - Year 1)
• Seminar in Groups and Organizations (Topical Seminar - Year 1 or 2)
• Human Judgment and Decision Making (SDS*)
• Behavioral Economics (SDS)
• Group and Decision Experiments in Economics and Psychology (SDS)
• ProSocial Behavior (Psychology)
• Cross Cultural Psychology (Psychology)
• Graduate Seminar in Groups (Psychology at Pitt)

Macro Organizational Behavior and Theory

• Seminar in Organizational Theory (Core Course - Year 1)
• Learning Processes in Organizations (Topical Seminar - Year 1 or 2)
• Special Topics in Organizations (Topical Seminar)
• Fundamentals of Social Network Methods (Heinz School)
• Intermediate Social Network Methods (Heinz)

Methods and Statistics

• Seminar in Behavioral Research Methods (Year 1)
• Experimental Design for Behavioral and Social Sciences (Statistics)
• Linear Models and Experimental Design (Statistics)
• Applied Econometrics I, II (Heinz School)
• Econometric Theory and Methods I, II (Heinz School)
• Statistical Analysis I, II (Psychology at Pitt)
• Multivariate Statistics (Pitt PSYED)
• Applied Regressions Analysis (Pitt PSYED)
• Hierarchical Linear Models (Pitt PSYED)
• Structural Linear Models (Pitt PSYED)

*Social and Decision Sciences

First-Year Paper

The doctoral program recommends an informal first draft of the paper be completed by July 1 of the first year following entry into the program. At a minimum, this draft would include a problem statement, relevant literature review, and basic design of the study.

A completed draft of the first year paper must be submitted to the two faculty readers by August 1 of the first year following entry into the program. Completed here means a reasonable idea has been developed and studied, and the paper is on track for completion by August 31 of the same first summer. Students are expected to spend the summer working on this paper.

In general, the summer is a critical time for students to work with faculty on research, and students are expected to be working on their research all year, including summers. The student must complete the proposed study (or in the case of a very ambitious project, a part of the proposed study approved by the faculty readers) by the end of the summer after the first year. The final product will be evaluated for the third-semester review following the general evaluation guidelines set out by the Tepper School Ph.D. committee for first-year papers.

Second-Year Paper

The second-year paper is a research project that ideally will help the student work toward the development of a dissertation. The project can involve empirical research and/or theory development.

The paper should reflect the greater skill and sophistication of a second year student. Again, the topic should be a social science project with some clear, identifiable link to OBT. Again, the student must identify two readers for the paper. The student may ask one of the readers to be a primary reader, if the student so desires. At least one of the two readers should be on the OBT faculty. The primary reader does not have to be an OBT faculty member. The readers have primary responsibility for the supervision of the student's research and the evaluation of outcomes.

Qualifying Exams

The qualifying exam will be scheduled at the end of the third semester in residence. Students take two exams: micro and macro.

The questions covered in these exams will draw from the content of all the OBT doctoral courses offered in the three preceding semesters. However, we expect students to begin reading the current literature in the field (e.g., in publications like Academy of Management Journal, Academy of Management Review, Administrative Science Quarterly, American Journal of Sociology, American Sociological Review, Journal of Applied Psychology, Research in Organizational Behavior, and Organizational Behavior and Human Decision Processes).

Students should be aware of classic work in the field as well as work appearing in the recent literature that pertains to the topics covered in the required courses.

Teaching Requirement

In order to develop teaching skills in preparation for an academic position, students are required to deliver a course or recitation section. Typically, Ph.D. students in OBT teach a section of Organizational Behavior I, the required course in the undergraduate Business Administration program.

The opportunity to teach often occurs during the summer session after the second, third, or fourth year. Students typically work as teaching assistants to faculty, grading and assisting more generally, in preparation for this requirement. However, the teaching requirement cannot be fulfilled by working as a TA.

Dissertation

The major requirement for the Ph.D. degree at Carnegie Mellon is the doctoral dissertation, which must be a significant research accomplishment representing a clear contribution to knowledge and containing material worthy of publication. In the Tepper School doctoral program, the dissertation may be either a monograph or a collection of related papers, depending on the nature and scope of a student's subject.

In OBT, a student works with the faculty to formulate ideas for the thesis. The student then forms a committee, usually composed of three to four faculty members from the student's major field and allied areas. One of these members serves as the Chair of the committee. At least one member of the committee must be a member of the OBT group.

Each student at the Tepper School writes and then presents a thesis proposal in a seminar with faculty advisors comprising the committee, other interested faculty, and other Ph.D. students. This seminar gives the student an opportunity to exchange ideas with faculty members and other students and to collect valuable suggestions and advice on the structure and direction of the dissertation. If the faculty approves the dissertation topic, the dissertation committee is formally appointed. The committee guides the student in completing the dissertation and in developing research skills that meet the highest professional standards.

The dissertation and the final oral defense should demonstrate a student's command of the field of study, independence in defining and solving a problem in that field, and skill in communicating ideas.

The Tepper School's doctoral program in operations research (OR) is designed to encourage students to make contributions toward basic scientific knowledge in the area. This knowledge can take several forms including:

• The derivations of fundamental results of an analytical or mathematical nature that lead to the development of algorithms for aiding decision-making
• The development of new analytical models appropriate for management science applications in areas such as Marketing, Operations, and Finance
• Controlled experimentation that leads to empirical results that make efficiency comparisons possible among algorithms

A major goal of the program is to train students to recognize operations research problems in real-world situations, and to give them the opportunity to learn about the deployment of operations research models in one or more of these substantive areas. Towards this goal, the program provides the opportunity to develop knowledge of functional areas of business to which optimization can be applied such as Marketing, Operations and Finance. There is a rich tradition of graduates from the program going on to successful careers in these areas both in academia (in business schools, engineering schools in IE and OR departments as well as in Math and Computer Science departments) and industry. 

Course of Study

The basic operations research courses offered include: linear, nonlinear, integer and dynamic programming; graph theory and network optimization; convex optimization and convex analysis; and stochastic models. Each course is taught by a faculty member who is actively pursuing research in the subject area. Since classes are usually small, students frequently meet informally with their instructors. The third semester competence examination is based on the areas covered in these courses.

Research

The research papers assigned for the first and second summers of graduate study are designed to give students an early introduction to research work. The paper may be done individually or jointly with other students or faculty members. Easy interaction in the Tepper School with researchers in the other areas of business and economics and in such related areas as computer science, machine learning, and statistics encourages the application of operations research in imaginative new directions.

In many cases, work on these papers leads to the work on the Ph.D. dissertation, which can begin as soon as the student has passed the third-semester qualifying examination.

Almost invariably, by the end of their second year, if not earlier, students have already worked on professional problems with some of the faculty. For this reason, student working papers written in collaboration with a faculty member are common.

Our History

Carnegie Mellon has pioneered several important developments in both theoretical and applied operations research. Geometric programming, chance constrained programming, and the applications of linear programming to capital budgeting and cost management were among the accomplishments of the '50s and early '60s. Since 1968, when the doctoral program in operations research was started, the Tepper School has initiated several new developments in integer and non-convex programming, enumerative methods, cutting plane theory, disjunctive programming, constraint programming, network design, algorithm design, machine learning, data mining, and scheduling models. 

Recently, the group has pioneered advances in Approximation Algorithms for Network Design, as well as theory and applications of Modern Convex Optimization. Examples on the Selected Research Topics page illustrate the basic research currently in progress, and examples of new operations research applications can be found elsewhere on the Doctoral Program website.

Research Topics

• Mixed-Integer Programming
• Convex Optimization
• Benders Decomposition
• Branch and Price
• Approximation and Online Algorithms
• Network Design
• Analytical Models in Marketing and Operations
• Connections with Artificial Intelligence
• Interplay between Estimation and Optimization
• Bayesian Optimization
• Massively Distributed and Parallel Algorithm Design
• Machine Learning
• Cultural Factors
• Ethics of Artificial Intelligence

Many of our students are very active in the Carnegie Mellon INFORMS Student Chapter.

To learn about the joint PhD program in Algorithms, Combinatorics and Optimization, please visit the webpage. 

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates.

Requirements

The requirements for the Ph.D. in Operations Research include:

• Course work
• Third semester qualifying examinations
• First and second year papers
• Ph.D. dissertation

A normal course load involves taking 120 units during the first two years, including core Operations Research courses and a minor area of concentration. Courses that run over a mini are worth 6 units.

The purpose of the minor requirement is to broaden the students’ knowledge to make them capable of teaching a wider range of courses and to enhance their research capabilities. The needs and preferences of individuals are recognized; therefore, the courses they take can vary. Examples of areas of concentration for the minor requirement include:

• Statistics
• Computer Science
• Operations Management
• Finance
• Marketing
• Machine Learning

Students with appropriate preparation prior to their entry to the program may take the qualifying exams prior to the third semester point if they choose, but they must take the entire set of qualifiers in the Operations Research area of study. The qualifying exams consist of eight questions, five of which are mandatory while the other three are chosen from a list of six.

Core Courses

• Linear Programming
• Network Optimization I
• Integer Programming
• Stochastic Processes (e.g. Performance Modeling)
• Modern Convex Optimization

Plus three from the following list: 

• Network Optimization II
• Convex Analysis
• Constraint Programming
• Advanced Linear Programming
• Advanced Integer Programming
• Nonlinear Programming
• Statistical Foundations of Operations Research
• Algorithms in the Real World [CS 15-750] 

Additional Electives in Operations Research at the Tepper School

• Combinatorial Optimization
• Convex Polytopes
• Dynamic Programming
• Open Source Software for Optimization
• Social, Economic and Information Networks

Students are encouraged to also take electives in other departments on campus, such as Computer Science or Mathematical Sciences.

Example of a Course Sequence

Year 1 

M1: Linear Programming, Network Optimization I, Performance Modeling

M2: Network Optimization II OR Advanced LP, Constraint Programming OR Convex Analysis, Performance Modeling

M3: Integer Programming, Convex Optimization, course in minor area

M4: Advanced IP, Nonlinear Programming, course in minor area

Year 2

M1: Elective, course in minor area

M2: Network Optimization II OR Advanced LP, Constraint Programming OR Convex Analysis

M3: Elective, course in minor area

M4: Elective, elective

The goal of the doctoral program in Operations Management is to train researchers and future faculty to develop scientific solutions to the problems currently being faced by operations managers.

Operations Management covers a broad range of topics as found in:

• Online platforms and sharing economy
• Health care management
• Supply chain management
• Sustainable operations
• Service operations
• Omni-channel retail
• Global operations and strategy
• Inventory control
• Just-in-time manufacturing
• Revenue management
• Commodity and energy merchant operations
• Real options
• Innovative business models

Research

Faculty research interests range from quantitative modeling to empirical studies using tools from operations research, mathematical programming, applied stochastic processes, simulation, artificial intelligence, statistics, econometrics, and economics.

The Tepper School has a long tradition of outstanding doctoral education in all branches of management. The business school is strongly committed to manufacturing and operations management as evidenced by a strong MBA program in production and operations management (we have always been in the top two in major surveys) as well as an excellent Ph.D. program.

More generally, the Tepper School at Carnegie Mellon is committed to quantitative management research and has made innovative contributions leading to several Nobel Prizes in Economics, and the faculty in Operations Research have won the Frederick W. Lanchester Prize and the John Von Neumann Theory Prize (awarded by INFORMS).

Cross-Campus Collaboration

The Tepper School has close ties working with the Carnegie Mellon College of Engineering in topics including energy and green design and the School of Computer Science and Department of Mathematical Sciences in jointly administering the graduate program in Algorithms, Combinatorics and Optimization. The school partners with the CMU Robotics Institute in work involving artificial intelligence and the joint management of manufacturing and automation program. Interdisciplinary collaborations also include other schools and research centers across the CMU campus such as the Department of Statistics and the Heinz School of Public Policy and Management. Students have significant flexibility in conducting research with and taking classes from, faculty in these schools.

Interdisciplinary Approach

The Ph.D. program in Operations Management is small with an interdisciplinary outlook. Students benefit from strong quantitative training as well as close ties with industry. A broad range of core and elective courses provides the students with a business outlook that is uniquely possible. In fact, the breadth of research possibilities under one umbrella at our group is probably unmatched by any other Operations Management department in the country.

Specific Project Partnerships 

• Caterpillar
• IBM
• Amazon
• OrganJet
• EQT
• University of Pittsburgh Medical Center
• University of California, San Francisco Transplant Center
• Massachusetts General Hospital

Methodological Contributions

• Inventory Models
• Machine Learning
• Queueing Theory
• Stochastic Modeling and Optimization
• Mechanism Design
• Approximate Dynamic Programming
• Game Theory
• Queueing Games

Many of our students are very active in the Carnegie Mellon INFORMS Student Chapter.

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates.

Requirements

Ph.D. students in Operations Management must fulfill all of the general Tepper School Ph.D. requirements, in addition to any area specific requirements. 

A normal course load involves taking 108 units during the first two years, including core Operations Management courses.

Students with appropriate preparation prior to their entry to the program may choose to take the qualifying exams prior to the third semester, however, they must take the entire set of qualifiers in the Operations Management area of study.

Tracks

The OM PhD Program is organized into three tracks:

(I) Modeling and Methodology
(II) Modeling and Theoretical Analysis
(III) Modeling and Empirical Analysis 

The courses and qualifiers are organized according to these tracks, as illustrated in the following tables.

Qualifying Exams (Questions)

The Tepper School's doctoral program in marketing has a reputation of producing highly skilled and innovative researchers who are well grounded in the basic disciplines underlying marketing thought and who practice and create the state-of-the-art in marketing. Most go on to become faculty members at premier academic institutions throughout the world.

The Ph.D. program offers one of the most complete and solid sequence of Ph.D. courses among leading universities in the world. Students usually take one and a half years of required courses offered by the marketing, economics, psychology and statistics departments. After passing the qualifying exam at the end of one and a half years, they begin the research stage, find advisors according to their own research interests, and start writing their Ph.D. dissertation under the guidance of the advisors. Typically, it takes four to five years to complete the program and obtain the Ph.D. degree. In addition to rigorous course work, students benefit from the weekly seminars in which scholars from all over the world come present their most recent research. Students also have their own workshops in which they present their own research work. 

Research

The Tepper School boasts excellent faculty, specializing in adopting analytical, empirical and consumer behavior approaches to address fundamental marketing problems. Historically, Tepper School faculty and graduates have made fundamental contributions to marketing theory in the areas of brand-choice models, analytical models for marketing strategy, empirical structural models, conjoint analysis, marketing and operations management interface, marketing and information systems interface and theories of consumer behavior. 

A few examples of research topics that students and faculty members have recently worked on are: 

• How a manager allocates marketing resources to various alternatives like promotion, advertising and sales force. By developing decision support systems to aid managers, we hope to understand better the allocation problem to improve marketing efficiency.
• How to design new products while simultaneously considering consumer preferences, engineering constraints and design aesthetics.
• How to understand latent preferences of online customers by statistically analyzing their web browsing patterns.
• Psychological processes that drive consumer choice among alternative products. How we can help them make better decisions. 

Starting from 1971, the Tepper School has produced a significant number of leading researchers in marketing, including at least ten chaired professors at top-ten business schools and many other world-renowned marketing researchers (high ratio given the size). Recent students who graduated from the Tepper School marketing program have obtained faculty positions at top research schools like Chicago, Columbia, Duke, Stanford and New York University. More recent graduates have won dissertation awards from the the American Marketing Association, the Association for Consumer Research, and the American Psychological Association. 

Given the size of our Ph.D. program, these achievements of our Ph.D. alumni demonstrate the outstanding quality of our Ph.D. program and also win us the reputation as one of the best schools that produce the most promising marketing researchers. 

As a Ph.D. student of marketing at the Tepper School, you will notice a few things that distinguish your experience at the Tepper School.

Outstanding Training in Economics, Psychology and Statistics Foundations 

As a tradition, our students are required to obtain rigorous training in economics, econometrics, psychology and statistics. The comprehensive and rigorous training equips our students with a solid understanding of economics and psychology, the state-of-the-art research techniques, and cutting-edge approaches for solving fundamental research problems. Historically, this approach has had high payoffs - our students are not only capable of solving ground-breaking research problems using the most cutting-edge techniques, but also demonstrate great endurance in their future academic careers. 

Comprehensive Sequence of Marketing Doctoral Courses

We offer the most complete sequence of Ph.D. courses. You will find many Ph.D. courses offered by marketing faculties that cover their research expertise. These marketing Ph.D. courses progressively and comprehensively introduce cutting-edge research methodologies, the development of literature in each discipline, and the most recent research interest of each faculty member. Faculty are almost available 24/7 to work with Ph.D. students. They also spend an enormous amount of time preparing students for their job market. Most students continue working with faculty at CMU even after graduating and enjoy a lifetime of support and friendship from them. 

Close and Caring Working Relationship Between Faculty and Students

At the Tepper School, our most important mission is to produce the best Ph.D. students. We treat Ph.D. students as junior faculty and the excellent mentoring system guarantees enough time from faculty to each Ph.D. student. The school typically admits only a few students each year. The doctoral program is intentionally kept small in order to increase faculty-student interaction and to take advantage of the business school's resources. They develop, in close conjunction with the faculty members, flexible programs addressing their specific research interests. Our students have access to award-winning faculty—many of whom are leaders in their field. Our faculty works closely with students creating new knowledge on a daily basis with their students. 

Inspiring and Innovative Inter-Disciplinary Research Environment

Recognized for our unique interdisciplinary environment, students are often encouraged to work across departmental lines. As a result, our graduates have opportunities to engage in groundbreaking research and sharpen their ability to solve complex problems through leadership and collaboration. 

In summary, the marketing group has a strong commitment to research and devotes considerable resources to training future scholars. We emphasize the development of sophisticated, state-of-the-art research skills that are required to solve fundamental research problems and create new knowledge in a chosen area of marketing. The Ph.D. program welcomes applications from candidates from all countries with distinguished academic backgrounds who are interested in pursuing a career in research universities. Admission to the marketing program at the Tepper School offers the student an opportunity to continue in this tradition of high achievement and excellence. 

Research Topics

The research focus of our program directly translates in their early involvement in research projects. Our doctoral students work closely with faculty members to produce high quality research in several relevant marketing topics. 

• Behavioral and Experimental Economics
• Charitable Giving and Nonprofit Marketing
• Consumer Financial Decision Making
• Consumer Happiness/Satisfaction
• Electronic Commerce
• Hedonic Adaptation
• High Tech Marketing
• Judgement and Decision Making
• Micro-marketing
• Optimal Pricing Strategies
• Service Productivity and Performance Pay
• Sports Marketing and Celebrity Endorsements
• Structural Estimation Methods
• Two-sided Market Pricing

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates.

Requirements

Ph.D. students in Marketing must fulfill all of the general Tepper School Ph.D. requirements, in addition to any area specific requirements. 

The Marketing Ph.D. Program is organized into three tracks: 

(I) Consumer Behavior
(II) Empirical Modeling
(III) Analytical Modeling

Often, two or more tracks are combined. 

The courses that students take tend to organize into two categories: Courses for All Marketing Students and Courses Based on Track. One thing to note is that this list is just an example and course offerings change regularly. Make sure to consult the Marketing area representative about an appropriate course selection for you. 

Courses for All Marketing Students Include

Students are encouraged to take all marketing courses offered, which currently includes: 

• Analytical Models in Marketing (47-753)
• Analytical & Structural Marketing Models (47-744)
• Bayesian Statistics for Marketing (47-747)
• Multivariate Data Analysis (47-755)
• Empirical Models in Marketing (47-756)
• Structural Models & Quantitative Methods (47-757)
• Estimating Dynamic and Structural Models (47-952)
• Understanding the Consumer Mind (47-738)
• Topics in Consumer Behavior (47-739)

Courses Based on Track

The following is a table of potential courses based upon based upon tracks. Note that students typically do not take all of these courses, but rather select those that best fit their research interests. Course titles and numbers may change and are not always offered, students may wish to substitute similar courses when available. Also, the set of Marketing courses for the two modeling tracks are the same because 1) empirical students increasingly formulate theory-based models and 2) theory/analytical students increasingly empirically test and validate their conclusions.

Qualifying Exams Based on Track

Consumer Behavior Track

Students typically take two sets of exams: 

1. Marketing — Students are tested on the breadth of the Marketing area which includes material covered in the “Courses for All Marketing Students”, reading list, and seminar topics.
2. Social and Decision Science Qualifier Exams on Judgement and Choice — Course indicated with an * prepare you for this exam, but confirm with the SDS Department on schedules and preparations.

Empirical and Analytical Modeling and Tracks

Students typically take two sets of exams: 

1. Marketing — Students are tested on the breadth of the Marketing area which includes material covered in the “Courses for All Marketing Students”, reading list, and seminar topics.
2. Microeconomics I & II and Econometrics I & II

Within the Tepper School, Ph.D. students are not required to take courses, but they are required to pass qualifying examinations. Tepper School students (those in this joint program who matriculate through the Tepper School) take the following qualifying examinations:

• Microeconomics
• Econometrics
• Macroeconomics
• Public Economics

The microeconomics and macroeconomics qualifying exams are the same exams that all Tepper School Economics Ph.D. students take. The microeconomics exam covers Microeconomics I, Microeconomics II, Game Theory and Applications, and Economics of Contracts. The macroeconomics exam covers Macroeconomics I, Dynamic Competitive Analysis, and Computational Methods for Economics. Students in the joint program may satisfy the econometrics requirement in one of two ways. They may take the Tepper School qualifying examination in econometrics, or they may take the Heinz quantitative requirements course sequence and take a qualifying examination based on that course sequence. 

Students with appropriate preparation prior to their entry to the program may choose to take the qualifying exams prior to the third semester, however, they must take the entire set of qualifiers as outlined above. 

Commentary on Course Requirements

In large measure, the course requirements combine those of the separate programs. The changes are as follows: 

Tepper School

Students will have the flexibility to take either the Tepper School's or Heinz's econometrics sequences. 

Heinz

The research seminar requirement is reduced from a two to one course requirement. We anticipate that Public Economics will be taught in research seminar format. Further, we wanted to reduce the course work demands in an already demanding curriculum. Note that the research seminar requirement is similarly reduced in the joint statistics Ph.D. program. 

Please visit our Ph.D. Student Profiles page to view the profiles of our current doctoral candidates. 

Requirements

With a few modest expectations students will be required to meet the course, examination, and research requirements of both programs. 

Examination Requirements

Tepper students (those in this joint program who matriculate through Tepper) take the following qualifying examinations: 

• Microeconomics
• Econometrics
• Macroeconomics
• Public Economics

The microeconomics and macroeconomics qualifying exams are the same exams that all Tepper Economics Ph.D. students take. The microeconomics exam covers Microeconomics I, Microeconomics II, and Microeconomics III. The macroeconomics exam covers Macroeconomics I, Macroeconomics II, and Macroeconomics III. Students in the joint program may satisfy the econometrics requirement in one of two ways. They may take the Tepper qualifying examination in econometrics, or they may take the Heinz quantitative requirements course sequence and take a qualifying examination based on that course sequence. 

Students with appropriate preparation prior to their entry to the program may take the qualifying exams prior to the third semester point if they choose, but they must take the entire set of qualifiers as outlined above. 

Course Requirements 

Heinz course requirements include: 

• Ph.D. Seminar I, II, & III (90-901/902/918)
• Organizations (90-917) or Demography (90-912)
• 1 research seminar
• Seminar in Public Economics

Four course Econometrics/Statistical Methods Requirement: 

This requirement can be met by taking a variety of graduate level courses from Tepper, Heinz, and the Department of Statistics. These courses include: 

• Statistical Theory for Social and Policy Sciences (Heinz, 90-905)
• Introduction to Econometric Theory (Heinz, 90-906)
• Econometric Theory and Methods (Heinz, 90-907)
• Econometrics I (Tepper, 47-811)
• Econometrics II (Tepper, 47-812)
• Econometrics III (Tepper, 47-813)
• Regression Analysis (Statistics, 36-707)
• Linear Models and Experimental Design (Statistics, 36-708)
• Discrete Multivariate Analysis (Statistics, 36-720)
• Continuous Multivariate Analysis (Statistics, 36-722)
• Time Series Analysis I (Statistics, 36-728)
• Time Series Analysis II (Statistics, 36-730)

In addition, students must pass a qualifying examination based on the material in the Heinz sequence of 90905, 90-906, and 90-907 or the Tepper sequence of 47-811, 47-812, and 47-813. 

Commentary on Course Requirements

In large measure, the course requirements combine those of the separate programs. The exceptions are as follows: 

• Tepper School of Business students will have the flexibility to take either Tepper School or Heinz College econometrics sequences.
• The Heinz College research seminar requirement is reduced from a two to one course requirement. We anticipate that public Economics will be taught in research seminar format. Further, we wanted to reduce the course work demands in an already demanding curriculum. Note that the research seminar requirement is similarly reduced in the joint statistics Ph.D. program.

Because this is a joint program, the requirements to complete it successfully include requirements from both the Tepper School of Business (Tepper) and the Department of Social and Decision Sciences (SDS). However, because of the overlap in these two disciplines, many of the requirements for each program apply to the other (e.g., one of the two summer research papers required by Tepper will also satisfy the SDS research paper requirement).

The field of Behavioral Economics was pioneered by our own Carnegie Mellon faculty Herbert Simon (a Nobel Prize winner in Economics) and George Loewenstein. While Behavioral Economics started as a small movement in the 1970s, it has made an enormous impact on academic research and research in Behavioral Economics papers regularly appears in the top economics journals. Behavioral Economics research has been used to help governments enact better public policy and operate more efficiently, to help businesses improve their profitability, and to help individuals make better decisions.