Graduate Schools of Business
Высшая Школа Бизнеса
Жоғары Бизнес Мектебі
PhD in Business Administration
Homepage → Academic programs → PhD in Business Administration
PhD in Business Administration Program is designed for students who aspire to become faculty members at leading academic institutions or conduct business research in relevant organizations.
PhD in Business Administration Program is designed for students who aspire to become faculty members at leading academic institutions or conduct business research in relevant organizations.
ACADEMIC CALENDAR
PhD in BA Learning Outcomes
On successful completion of the PhD in BA program, the students will be able to:
1. Critically analyze, evaluate, and synthesize new and complex ideas;
2. Demonstrate a systematic understanding of their field of expertise (e.g., Accounting, Finance, Management, Marketing, and Strategy) and mastery of the skills and methods of research associated with that field;
3. Conceive, design, implement, and adapt a substantial process of research with scholarly integrity and concern for the high ethical standards;
4. Generate original research that extends the frontier of knowledge by developing a substantial body of work, some of which could merit national or international refereed publication;
5. Communicate authoritatively and with professional integrity about their field of expertise (e.g.,Accounting, Finance, Management, Marketing, and Strategy) with others such as their peers, the larger scholarly community, and society in general through research and teaching.
1. Critically analyze, evaluate, and synthesize new and complex ideas;
2. Demonstrate a systematic understanding of their field of expertise (e.g., Accounting, Finance, Management, Marketing, and Strategy) and mastery of the skills and methods of research associated with that field;
3. Conceive, design, implement, and adapt a substantial process of research with scholarly integrity and concern for the high ethical standards;
4. Generate original research that extends the frontier of knowledge by developing a substantial body of work, some of which could merit national or international refereed publication;
5. Communicate authoritatively and with professional integrity about their field of expertise (e.g.,Accounting, Finance, Management, Marketing, and Strategy) with others such as their peers, the larger scholarly community, and society in general through research and teaching.
PhD in BA students will typically be assessed according to the following assessment methods:
Grades
Papers
Surveys
Conferences
Seminars
Thesis
Grades
Papers
Surveys
Conferences
Seminars
Thesis
Successful completion of the PhD program requires the student to progress through the necessary stages:
1. Satisfactory application to the program.
2. Satisfactory completion of all required coursework in the program.
3. Successfully complete PhD qualifying examination.
4. Successfully defending a proposal for a PhD thesis project.
5. Successful viva voce examination of thesis by examiners.
6. Final submission of the written thesis.
1. Satisfactory application to the program.
2. Satisfactory completion of all required coursework in the program.
3. Successfully complete PhD qualifying examination.
4. Successfully defending a proposal for a PhD thesis project.
5. Successful viva voce examination of thesis by examiners.
6. Final submission of the written thesis.
The program comprises the following major aspects:
- 12 courses:
2) 3 Subject Specific Core Courses
3) 2 Elective Courses
2. Submission and presentation of 2 Research Papers (in Year 1 and Year 2 Summer Semesters) as part of the requirements of the Core Research Skills I and II courses.
PhD Comprehensive Examination (Summer of Year 2).
Submission of an Annual Progress Review at the end of Years 1, 2, and 3.
Presentation of a Thesis proposal (Fall of Year 3).
Defence and submission of a Thesis in Year 4.
The overall 4-year program equates to 240 ECTS.
Before the start of Year 2, during the summer of year 1, each student will choose a primary PhD advisor.
- Foundations of Social Science Research
- Mathematical Economics
- Microeconomic Theory
- Core Research Skills I
- Advanced Qualitative Methods
- Advanced Quantitative Methods
- Summer Research Paper
- Subject Specific Course I
- Subject Specific Course II
- Subject Specific Course III
- Core Research Skills II
- Elective I
- Elective II
- Summer Research Paper
- PhD Qualifying Examination
- Thesis Proposal Presentation
- Final Thesis Submission
- Final Thesis Defense
- Two successful GTAs
- GSB Research Seminars
- Research projects
Year 1 Curriculum
This course considers the relationship between the dominant philosophical perspectives which inform social science research and the practice of doing social science research. It provides the foundations for learning about social science research by enabling students to justify and explain their own epistemological choices. The course highlights how these choices impact upon questions of research design and method. The course introduces philosophical/theoretical concepts alongside practical issues of research method choice and design.
In this course, you will learn the mathematical methods at the heart of microeconomics and micro-funded macroeconomics. These are basically the optimization methods needed to formalize the rationality of economic agents’ choices. We will start with a review of the linear algebra, vector spaces, and inner product spaces framework needed to be able to use differentiability properties and work with linear and quadratic approximations to get the first and second order conditions characterizing, sufficiently or necessarily, the optimal choices. Then we will cover systematically, in finite-dimensional spaces, the problems of unconstrained optimization, optimization under equality constraints or the problem of Lagrange, optimization under inequality constraints and the Kuhn-Tucker conditions, the sensitivity of the solutions to the parameters of the problem through the Envelope Theorem for all three cases, the interpretation of the multipliers associated to the constraints, the duality properties of linear programs, and finally optimization over an infinite horizon, both using the first order conditions leading to the Euler equation of the problem, and the Bellman functional equation following from the dynamic programming approach.
In this course, you will learn the fundamentals of how to model the behavior of economic agents and their interactions through markets. We will cover the core of the conceptual framework at the heart of most of economics of competitive markets, namely choice theory, consumer’s choices, classical demand theory, choice under uncertainty, the existence of a general equilibrium in and Arrow-Debreu economy of competitive markets and its efficiency properties, the First and Second Welfare Theorems, trading in sequential markets, Radner equilibria in sequential markets economies with financial assets, incompleteness of markets, infinite horizon economies with either “infinitely-lived” agents or dynasties, or with a sequence of overlapping generations of households.
This course is designed to introduce students to business research and to develop student’s research and analytical skills. Students are introduced to the theory and logic of research, the ethics that guide the research process, and to the range of research methods generally employed in business research. Attention will be paid to research design, data collection, elementary data analysis, and report writing. The course includes discussion of specific methodological approaches. The emphasis is on providing practical knowledge of the research process and in preparing students to conduct their own basic research projects. Students will leave the course with a better understanding of how to conduct their own research as well as a better understanding of how to evaluate the research of others. The course will prepare students for advanced research methods courses in their chosen field.
This course is aimed to provide a detailed overview of qualitative research methods and techniques used in social sciences, including public policy and public administration. Although the course will focus on different types of research designs, conceptual models, techniques and sampling procedures, much attention will be given to data analysis in qualitative research. In this course, students will learn to critically choose and apply appropriate methods for conducting original research in the sphere of social sciences. Most importantly, students will learn how to use and analyze data with the help of Nvivo Pro software applied in qualitative research in the lab tutorials. Students will be exposed to exemplary scholarly publications with qualitative studies and be involved in original research projects to demonstrate acquired research skills. It is expected that students have some knowledge of conducting research. Further to this course, students will be able to develop their knowledge of methodologies further in their area of specialization in the Core Research Skills course.
In an increasingly digitalised environment, data availability offers opportunities not only to empirically test theories through statistical analyses, but also to discern behavioural, associative or intrinsic data patterns and enable or even inspire theory development. Familiarity with probabilistic and statistical thinking and exposure to alternative types and sources of data enables researchers and practitioners to broaden their horizons when considering alternatives in diagnosing problems and developing explanations/solutions. Quantitative Research Methods introduces students to a variety of building-block statistical / data analytic techniques and gets them to develop genuine understanding and judgment about when and why to use each of them. The course extends in two semesters: the first semester covers the foundational concepts and techniques for quantitative analysis, while the second builds on this material to introduce and explain the use of an array of essential multivariate methods. On completion of this course, students will be able to work: a) from problem formulation to data extraction/collection and analysis; and b) from existing data to pattern recognition and problem identification. Further to this course, students will be able to develop their knowledge of methodologies further in their area of specialization in the Core Research Skills course.
The course is designed to be accessible to all students regardless of their ability to access any on-campus teaching events that may be offered. Where on-campus events are provided, students are expected to attend but alternative provision will be available for students who are unable to do so for health or similar reasons.
The course is designed to be accessible to all students regardless of their ability to access any on-campus teaching events that may be offered. Where on-campus events are provided, students are expected to attend but alternative provision will be available for students who are unable to do so for health or similar reasons.