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Concentrations

The Ph.D. Program currently offers specialization in the following three major areas:

The field of Management and Organization is typically considered as comprising a division between a more macro orientation geared towards studying organizations and their higher level aggregates as well as the more micro-level concerns focusing on individual and group behavior within organizations. The Management and Organization specialization within the Ph.D. program at Sabanci University can accommodate students who wish to pursue any one of these lines of research as well as those who may wish to seek ways to integrate the two.

The curriculum of the Management and Organization program firstly provides a strong background in conducting scholarly research. Building on this, students then take courses that specifically focus on organization theory, strategic management, organizational behavior and cross-cultural psychology. Students are then provided with the opportunity, through elective courses, to pursue their specific interests and develop a research agenda to be examined during dissertation work.

Required Courses:

MRES 601 - Research Methods in Management and Organization Studies:

Research Methods in Management and Organization Studies This PhD seminar provides a foundation for theory building and empirical analysis in the study of organizations. Rather than focus on particular statistical or analytical methods, the goal is to provide participants with a rigorous grounding in the scientific approach to constructing theoretical arguments and designing appropriate empirical tests. The course is organized around the question of how to do good research. Topics to be covered include common threats to validity in research design, decisions regarding the choice of samples and settings, measurement issues such as reliability and validity, estimation methods, data collection tools, and ethics in planning, conduct, and publication of research. The seminar thus serves as a complement to other basic and advanced research method courses, and will develop skills needed to: 1. build and analyze theoretical arguments 2. design effective tests of theory 3. understand the interplay between theory building and theory testing Students will get some experience critiquing the methodology used in published studies and hopefully develop some idea about how to start conducting their own dissertation research.

 

MRES 609 Professional Development Seminar I or BAN 599 Graduate Seminar:

Professional Development Seminar I This is a weekly seminar (coordinated by a faculty member or a faculty team) that all doctoral students are expected to a attend and actively participate. The objectives are to orient the student to research traditions in sub-fields of management studies and to the professional life of an academic. With regard to the first objective students are exposed to current scholarly research through presentations by faculty members and invited speakers as well as the work and experiences of their doctoral colleagues. There are also sessions that specifically explore the current state of research in Turkey in particular areas of management studies. With regard to the academic profession there are opportunities to address issues related to developing publishable work, the review process, and refereeing as well as getting prepared for teaching responsibilities

Graduate Seminar This seminar course provides a non-credit framework for the continuous monitoring and collegial discussion of MA students' thesis research and writing, which they are expected to accomplish under the supervision of a Faculty member from the relevant field.

 

GR 501M Academic Practices and Development:

Academic Practices and Development This course introduces fundamental principles in teaching and learning for graduate students in the event that they choose a career in academia.In addition, this course acculturates students to the practices and culture of Sabanci University. Through a series of workshops, graduate students will learn about best practices in teaching and learning, ethics, publication of research and how to apply them to the current student population at Sabanci University. Once students have participated in this series of workshops, they will help out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 502M Academic Practices and Development  2:

Academic Practices and Development 2 This course is a follow-up to GR 501M and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. This course will enable graduate students to reflect on their first semester helping out with a course, plan for the coming semester, and develop new skills in areas such a teaching with technology and grading. Through a series of workshops, graduate students will learn about best practices in teaching and learning, and how to apply them to the current student population at Sabanci University. Students will continue to helping out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 555M Academic Writing for Graduate Students:

Academic Writing for Graduate Students This course aims to enhance the academic communication skills of graduate students with the goal of facilitating research output. To this aim, this course helps master’s and doctoral students develop skills essential for writing academic papers and theses in English. It provides guidelines on writing for the rhetorical genres characteristic of academic writing in the social sciences and humanities such as literature review, abstract, proposal, article for publication, and thesis. Students will also help out with one or more courses offered at the University.

 

GR 503M Academic Practices and Development  3:

Academic Practices and Development 3 This course is a follow-up to GR501M and GR502M, and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. Students in this course will be observed by a supervisor or another observer at least once per semester in order to provide feedback on the student’s teaching performance as well as have the option to participate in additional professional development activities. Students will continue helping out with one or more courses offered at the University, which will allow them to apply the principles learned in this and previous courses.

 

Core Area Courses: (For students having MS Degree)

MGMT 602 Doctoral Seminar in Strategic Management:

Doctoral Seminar in Strategic Management This course involves a critical review of theory and research in the field of strategic management. The scope of the course is comprehensive, encompassing the following domains: strategic content, strategic processes, top executives, and corporate governance. Particular emphasis is placed on empirical study of strategic issues. The course is intended for doctoral students who expect to conduct research in strategic management or related areas (e.g., organizational theory, organizational behavior, marketing strategy, corporate finance, industrial organization, sociology of organizations, operational strategy). Each session we will examine a sub-field of strategic management. The topics include origins of the field of strategic management, conceptualizing and operationalizing strategy, industrial and organizational economics view of strategy, resource-based view of the strategy, learning and knowledge-based view of strategy, corporate level strategy (diversification and M&A/divestitures), international strategy and strategy in emerging markets, top executives and the upper-echelons perspective, governance and agency theory, strategic decision making, and strategy and organizational design. Our approach will typically involve reading the seminal works, synthesizing the theories/perspectives on the topic and examining in depth several empirical works.

 

ORG 625 Cross Cultural Organizational Psychology:

Cross Cultural Organizational Psychology This course focuses on cross-cultural psychology with an emphasis on behavior in organizations. This class aims to critically examine the cultural assumptions embedded in existing organizational theories, which typically have emerged from the US. Secondly, and in line with the first aim, it tries to sensitize students to the issue of contextual diversity in which organizations and their members operate as well as creating some awareness about perspectives that have something to say about societal variation. To this end, conceptualizations of culture, theoretical perspectives linking culture to behavior, methodological issues in conducting cross-cultural research, as well as the research on cross-cultural differences will be covered. Specific focus will be on understanding how culture affects basic psychological processes, including cognition, emotion, and motivation and their implications in terms of micro organizational studies.

 

ORG 612 Organizational Behavior:

Organizational Behavior This seminar is designed to provide students with a broad overview of the major topics in the field of organizational behavior (OB). The course starts off with a critical introduction to the field of OB, followed by an orientation to research on individual differences, job attitudes such as job satisfaction and organizational commitment, motivation theories, psychological contracts and interorganizational trust. The course then proceeds to cover other OB topics like group dynamics, leadership, and organizational culture, and the literature on the relationship between these variables and processes and various job outcomes such as citizenship behaviors, and various job outcomes such as citizenship behaviors.

 

ORG 613 Organization Theory:

Organization Theory The central objective of this course is to introduce students to perspectives on studying management and organisational phenomena. It aims to develop a critical appreciation of the historical evolution and the current state of management and organisation studies. The former part of the course is devoted to charting the domain and concerns of organisational analysis and deals with issues like organisations and their environments, goals and effectiveness, power and control, their and work, and forms and structuring of organisations. The course then proceeds to a review and discussion of major perspectives and research programmes in organisational analysis. The student is thus given an opportunity to develop an understanding of the central features of different perspectives as well as appreciating the nature of ongoing controversy and debate among competing viewpoints. The review of earlier traditions like scientific management, human relations and contingency theory are followed by critical perspectives of the time, namely Marxist and action frames of reference. More recent research traditions to be reviewed include resource dependence, institutionalist, and ecological perspectives as well as those that stem from neo-isntitutionalist economics and economic sociology. The course finally considers more recent alternative traditions like interpretive, critical realist, and postmodern approaches.

 

Core Area Courses: (For students having BS Degree)

POLS 529 Methods and Scope of Political Analysis:

Methods and Scope of Political Analysis This course provides an introduction to philosophy of social sciences, various methodological approaches in political science and research methods and analysis. Components of research design, measurement, validity, data collection strategies and logic of inference are discussed. Various research design examples are provided from the recent political science literature and students are exposed to research process, article evaluation and thesis proposal writing. It also aims to expose students to ethical considerations in research and publishing.

 

PHIL 501 Philosophy of Social Sciences:

Philosophy of Social Sciences This course is an introduction to the main issues and approaches in the philosophy of social sciences, with a focus on questions of methodology. These include whether social sciences employ a methodology different from that of the natural sciences; whether explanations in terms of reasons differ in any way from those in terms of causes; the nature of social reality; the relationship between individuals and social structures; the debate between methodological individualism and methodological holism; whether social sciences are value- free or not and the problem of objectivity. General approaches to be discussed are positivism, realism, the hermeneutical-interpretive and critical schools. These approaches and issues will be exemplified in the context of various social scientific disciplines.

 

ORG 501 Organizational Behavior and Leadership:

Organizational Behavior and Leadership Organizational behavior is the study of people in organizations-how and why they think, feel and act the way they do. The field, which borrows extensively from the social sciences, includes but is not limited to, topics such as motivation, decision making, leadership, organizational culture, communication, organizational conflict, power and negotiation, team processes, organization change, structure and change. This course is based on a belief that social science has much to offer the practicing manager and that becoming an effective manager of others requires increasing our own self-awareness and a portfolio of managerial skills. Thus, the course combines traditional lectures with the use of cases, group projects and experiential exercises.

 

MRES 604 Applied Econometrics:

Applied Econometrics Applied Econometrics The purpose of this course is to provide students with state of the art econometric methods for empirical analysis of micro data (individuals, households, firms etc.). Issues related to specification, estimation and identification of different models with cross-section and panel data will be studied. The course has an emphasis both on the econometric techniques and their applications to different topics. Students are expected to read assigned papers and undertake numerous practical assignments using a modern econometric software package.

 

MRES 602 Multivariate Statistics:

Multivariate Statistics This course covers the basic multivariate techniques that are currently used in various areas of social sciences. The learning goal for students is to have a conceptual understanding of each statistical technique, be able to apply the correct technique to any given set of data, properly interpret the output of statistical computer packages, and understand and critique scientific papers that use these techniques. The course begins with an introductory session on matrix algebra, sample geometry and random sampling. Next, the properties of the multivariate normal distribution are examined with an emphasis on how to make inferences about multivariate means and to compare several multivariate means (MANOVA). Other topics that are covered include analysis of covariance structures including principal components, factor analysis and canonical correlation analysis as well as classification and grouping techniques such as discriminant analysis, clustering and multidimensional scaling.

 

Elective Courses:

(For MS degree students, 15 credits and 5 courses are required with advisor's approval)

Course CodeCourse NameSU Credit

MGMT 611

Qualitative Research Methods3

MRES 602

Multivariate Statistics3

MRES 604

Applied Econometrics3

ORG 615

Human Resources Management3

ORG 627

Special Topics In Organizational Analysis I3

ORG 628

Special Topics in Organizational Analysis II3

ORG 629

Special Topics in Organizational Behaviour I3

ORG 630

Special Topics in Organizational Behavior II3

ORG 631

Special Topics in HRM I3

ORG 632

Special Topics in HRM II3

PHIL 501

Philosophy of Social Sciences3

Elective Courses:

(For BS degree students, 24 credits and 8 courses are required with advisor's approval)

Course CodeCourse NameSU Credit

MGMT 602

Doctoral Seminar in Strategic Management3

MRES 611

Qualitative Research Methods3

ORG 612

Organizational Behavior3

ORG 613

Organization Theory3

ORG 615

Human Resources Management3

ORG 625

Doktoral Seminar in Cross Cultural Organizational Psychology3

ORG 627

Special Topics In Organizational Analysis I3

ORG 628

Special Topics in Organizational Analysis II3

ORG 629

Special Topics in Organizational Behaviour I3

ORG 630

Special Topics in Organizational Behavior II3

ORG 631

Special Topics in Human Resources Management I3

ORG 632

Special Topics in Human Resources Management II3

Business Analytics and Operations Management is a field that has emerged from the need of explicitly addressing the decision-making issues that managers confront regarding the operations function of their organizations. With its continuously evolving nature, and especially with the increasing presence of Big Data in our lives and the endless possibilities to make humanitarian and commercial use of it through data-driven business decision-making, it has expanded from its foundations to include a wide array of subjects such as operations and manufacturing strategy, service operations, pricing, as well as supply chain design and management.

The Ph.D. program curriculum has been designed so that the students are exposed not only to traditional research foundations rooted in quantitative methods and statistics, but also to research methodologies from other management disciplines such as organization studies. Given this perspective, students are then provided with the opportunity to focus on their specific interests and develop a research agenda to be examined during their dissertation work. The flexibility of choosing a curriculum with cross-discipline courses not only increases the variety of academic exposure in this field, but also prepares our students in the most extensive and effective ways for their future careers.

Required Courses:

OPIM 613 Operations and Decision Analytics:

Operations and Decision Analytics This course focuses on decision problems of developing, producing, and delivering goods and services. The purpose is to provide students an exposure to the spectrum of operations management field, the nature of the related decision problems, and applications of various predictive and prescriptive analytical tools. The topics include, but not limited to, process and product design, logistics and transportation, location analysis, production/inventory management, pricing and revenue management, service operations, sustainability, and behavioral operations.

 

MRES 609 Professional Development Seminar I or BAN 599 Graduate Seminar:

Professional Development Seminar I This is a weekly seminar (coordinated by a faculty member or a faculty team) that all doctoral students are expected to a attend and actively participate. The objectives are to orient the student to research traditions in sub-fields of management studies and to the professional life of an academic. With regard to the first objective students are exposed to current scholarly research through presentations by faculty members and invited speakers as well as the work and experiences of their doctoral colleagues. There are also sessions that specifically explore the current state of research in Turkey in particular areas of management studies. With regard to the academic profession there are opportunities to address issues related to developing publishable work, the review process, and refereeing as well as getting prepared for teaching responsibilities.

 

Graduate Seminar This seminar course provides a non-credit framework for the continuous monitoring and collegial discussion of MA students' thesis research and writing, which they are expected to accomplish under the supervision of a Faculty member from the relevant field.

 

GR 501M Academic Practices and Development:

Academic Practices and Development This course introduces fundamental principles in teaching and learning for graduate students in the event that they choose a career in academia.In addition, this course acculturates students to the practices and culture of Sabanci University. Through a series of workshops, graduate students will learn about best practices in teaching and learning, ethics, publication of research and how to apply them to the current student population at Sabanci University. Once students have participated in this series of workshops, they will help out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 502M Academic Practices and Development  2:

Academic Practices and Development 2 This course is a follow-up to GR 501M and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. This course will enable graduate students to reflect on their first semester helping out with a course, plan for the coming semester, and develop new skills in areas such a teaching with technology and grading. Through a series of workshops, graduate students will learn about best practices in teaching and learning, and how to apply them to the current student population at Sabanci University. Students will continue to helping out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 555M Academic Writing for Graduate Students:

Academic Writing for Graduate Students This course aims to enhance the academic communication skills of graduate students with the goal of facilitating research output. To this aim, this course helps master’s and doctoral students develop skills essential for writing academic papers and theses in English. It provides guidelines on writing for the rhetorical genres characteristic of academic writing in the social sciences and humanities such as literature review, abstract, proposal, article for publication, and thesis. Students will also help out with one or more courses offered at the University.

 

GR 503M Academic Practices and Development  3:

Academic Practices and Development 3 This course is a follow-up to GR501M and GR502M, and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. Students in this course will be observed by a supervisor or another observer at least once per semester in order to provide feedback on the student’s teaching performance as well as have the option to participate in additional professional development activities. Students will continue helping out with one or more courses offered at the University, which will allow them to apply the principles learned in this and previous courses.

 

Core Area Courses:

 

Only one course from below can be taken:

BAN 505 Predictive Analytics:

Predictive Analytics This course introduces basic concepts and models of supervised and unsupervised statistical learning models. The topics include, multiple regression, logistic regression, classification, resampling methods, subset selection, the ridge, the lasso, tree-based methods, support vector machines, principal component analysis, and clustering.

 

CS 512 Machine Learning:

Machine Learning This is an introductory machine learning course that will aim a solid understanding of the fundamental issues in machine learning together with several ML techniques such as decision trees, k-nearest neighbor, Bayesian classifiers, neural networks, linear and logistic regression, dimensionality reduction, clustering, SVM and ensemble techniques. Some more theoretical aspects such as inductive bias and VC dimension will also be covered.

 

OPIM 623 Empirical Methods in Operations Management:

Empirical Methods in Operations Management This course covers the basic principles of empirical theory building and theory testing in operations management context. There is an emphasis on the use of theories offered by economics and other management disciplines such as organization studies to describe, explain, and predict operations related activities and outcomes. Empirical research techniques such as case, survey, archival research is discussed based on examples from the literature. (Knowledge of Research Methods, Probability and Statistics is recommended)

 

Only one course from below can be taken:

MRES 603 Probability and Statistics:

Probability and Statistics This course covers the fundamental concepts for probability and statistics. In the first part of the course, the focus is on concepts including random variables, probability distributions, specific discrete and continuous distributions and their applications, expected values and conditional probability. This is followed by a review of the central limit theorem and the law of large numbers. After these fundamental topics are covered, the focus shifts to statistics and the use of statistics principles in different contexts. Topics such as sampling distributions, point and interval estimates, confidence intervals, hypothesis testing, parametric and non-parametric tests, analysis of variance and linear regression are presented. (Knowledge of Calculus is recommended)

 

MRES 604 Applied Econometrics:

Applied Econometrics Applied Econometrics The purpose of this course is to provide students with state of the art econometric methods for empirical analysis of micro data (individuals, households, firms etc.). Issues related to specification, estimation and identification of different models with cross-section and panel data will be studied. The course has an emphasis both on the econometric techniques and their applications to different topics. Students are expected to read assigned papers and undertake numerous practical assignments using a modern econometric software package.

 

ENS 505 Methods of Statistical Inference:

Methods of Statistical Inference The main objective of this course is to review the basic concepts of the theory of statistics and further develop understanding of some fundamental applied statistical methods. Our emphasis will be on applications of the theory in the development of statistical procedures. Practical applications of statistics to some problems in engineering and management will be given. Computational assignments will be given to help the students to understand the concepts and to have an opportunity to practice applying them. Computer aided analysis of data; fundamental concepts of statistics and related distributions; design of experiments and analysis of variance; regression and correlation analysis; methods for stationary time series data; linear methods for classification.

 

BAN 527 Descriptive Analytics:

Descriptive Analytics This course aims to provide a review of methods for statistical inference, and develop an understanding of how these tools can be applied in a variety of business problems. The emphasis of this course would be on applications, through practical examples and cases. A variety of statistical software will be introduced. Topics covered include descriptive statistics, probability distributions, hypothesis testing, regression, design of experiments and analysis of varience.

 

ECON 505 Quantitative Methods:

Quantitative Methods The course introduces students to research methods, analysis and design and aims to expose them to ethical considerations in research and publishing. Topics included are linear algebra; probability theory, random variables distributions, hypothesis testing, asymptotic distribution theory, estimation.

 

Only one course from below can be taken:

ENS 511 Engineering Optimization:

Engineering Optimization This course will cover optimization methods for solving engineering problems. The methods will include linear and nonlinear programming, integer programming, dynamic programming, network models and an introduction to metaheuristic algorithms. Special emphasis will be given to practical aspects.

 

OPIM 611 Mathematical Programming:

Mathematical Programming This course exposes students to the theory and techniques of deterministic mathematical programming. Linear programming and its extensions, integer programming and network flows are the main areas of focus.The purpose is to provide a strong theoretical basis required for creating mathematical models of real world problems of interest and also developing effective methodologies for their solution and implementation. To this end, the course also reviews computational complexity issues and discusses techniques for building efficient computational methods in combinatorial optimization along with associated theory such as duality, relaxation, decomposition and column generation.

 

IE 501 Linear Programming and Extensions:

Linear Programming and Extensions Theory of linear programming; convexity; simplex and algorithmic aspects; duality and sensitivity; computational issues; decomposition and column generation; introduction to integer and nonlinear programming.

 

Only one course from below can be taken:

IE 503 Stochastic Processes:

Stochastic Processes Poisson and renewal processes; discrete and continuous Markov chains; applications in queuing, reliability, inventory, production, and telecommunication problems; introduction to queuing networks and network performance analysis.

 

OPIM 615 Stochastic Modelling:

Stochastic Processes The purpose of this course is to expose students to principles and applications of Stochastic Processes, by building upon the concepts introduced in a previously-taken basic probability course. In the first half of this course, topics including Bernoulli and Poisson processes, discrete and continuous-time Markov chains, renewal process and their applications are covered. This is followed by other topics such as queuing theory and its applications, stochastic dynamic programming and random walks. Upon completion of this course, the students have an appreciation of analytical models as well as applications of Stochastic Processes. (Knowledge of Calculus, Basic Probability and Statistics is recommended)

 

Students with a bachelor's degree take 2 more of the following courses:

OPIM 501 Operations Management:

Operations Management Operations management deals with the design, production and distribution of goods and services. Managerial issues and decision problems include the design, planning, and control of processes at strategic and operational levels. Concepts and tools used in generating solutions to problems and their implementation aspects are discussed. Operating systems from different areas such as manufacturing, service, and transportation are exemplified to expose students to the similarities and differences in their characteristics. Topics include operations strategy, process design and improvement, quality management, capacity and supply chain management.

 

OPIM 523 Decision Models:

Decision Models The main goal of this course is to present the basic principles and techniques of mathematical modeling that will aid managerial decisions. With case analyses, assignments, and classroom discussions, students will learn the assumptions, limitations and the effective use of the analytical methods such as optimization and Monte Carlo simulation. The focus will be on model formulation and interpretation of results, not on mathematical theory. This course is designed for Sabancı MBA students with an interest in formal decision modeling. Therefore, the emphasis is on models that are widely used in diverse industries regardless of the functional areas.

 

OPIM 532 Supply Chain Management:

Supply Chain Management Supply chain includes all the parties involved in the production of goods and/or services including suppliers, distributors, and customers. Supply chain management emphasizes the importance of coordination between these different partners in a supply chain. This course introduces the concepts and methods for successful supply chain management. Activies such as demand forecasting, production and inventory planning; purchasing and distribution planning are covered. The importance of coordination is demonstrated through case studies and simulations.

 

BAN 500 Introduction to Business Analytics:

ntroduction to Business Analytics As an introductory course to the program, the course will cover topics on the conceptual framework of business analytics, various sectoral application areas and a general introduction to analytical methods used. The course will also cover success stories from different sectors where business analytics is applied, and big data analytics in general, including its application areas, as a new and emerging area of interest.

 

BAN 502 Introduction to Decision Making:

Introduction to Decision Making This course presents an overview of decision making support methodologies and emphasizes the design of decision support systems using management science models such as production planning, logistics, employee scheduling, stock trading simulation, and portfolio optimization. These systems are developed using Microsoft Excel and VBA. VBA fundamentals are also covered in the course.

 

Elective Courses:

(For MS degree students, 15 credits and 5 courses are required with advisor's approval)

Course CodeCourse NameSU Credit
BAN 500Introduction to Business Analytics3
BAN 502Introduction to Decision Making3
BAN 503Management Information Systems3
BAN 505Predictive Analytics3
BAN 520Markov Decision Process3
BAN 522Revenue Management3
BAN 601Advanced Predictive Analytics3
BAN 602Advanced Prescriptive Analytics3
CS 512Machine Learning3
CS 515Neural Networks3
CS 523Information Retrieval3
CS 525Data Mining3
CS 541Multimedia Information Processing3
ECON 502Microeconomics II3
ECON 605Industrial Organization3
IE 524System Simulation3
IE 545Production Systems Planning and Design3
IE 554Supply Chain Management3
IE 638Advanced Topics in Supply Chain Management3
OPIM 524Business Process Analysis and Design3
OPIM 612Research Methodology in Operations Management3
OPIM 614Supply Chain Planning and Management Models3
OPIM 617Discrete Event Simulation3
OPIM 690Independent Study3

Elective Courses:

(For BS degree students, 24 credits and 8 courses are required with advisor's approval)

Course CodeCourse NameSU Credit
BAN 500Introduction to Business Analytics3
BAN 502Introduction to Decision Making3
BAN 503Management Information Systems3
BAN 505Predictive Analytics3
BAN 520Markov Decision Process3
BAN 522Revenue Management3
CS 512Machine Learning3
CS 515Neural Networks3
CS 523Information Retrieval3
CS 525Data Mining3
CS 541Multimedia Information Processing3
ECON 502Microeconomics II3
ECON 605Industrial Organization3
IE 524System Simulation3
IE 545Production Systems Planning and Design3
IE 554Supply Chain Management3
IE 638Advanced Topics in Supply Chain Management3
OPIM 614Supply Chain Planning and Management Models3
OPIM 617Discrete Event Simulation3
OPIM 690Independent Study3

The Ph.D. specialization in Finance emphasizes rigorous analytical training and prepares students to pursue careers either in the academia or in the financial industry. Theoretical research in finance generally starts with economic models. Researchers aim to understand the mechanisms of the financial markets through these models. Understanding the causal relationships between different factors that shape the player’s decisions in financial markets provides a powerful tool for investors, firm managers, regulators and the other decision makers. The initial set of courses in finance, mainly taken from the economics program, emphasize the role of theoretical models to build such a framework. 

The finance specialization curriculum also stresses the importance of empirical methods that are used to test the predictions of the theoretical models. The empirical models discussed in the program are often used in investment, asset pricing, corporate finance, corporate governance and banking fields.

 

Required Courses:

MRES 601 - Research Methods in Management and Organization Studies:

Research Methods in Management and Organization Studies This PhD seminar provides a foundation for theory building and empirical analysis in the study of organizations. Rather than focus on particular statistical or analytical methods, the goal is to provide participants with a rigorous grounding in the scientific approach to constructing theoretical arguments and designing appropriate empirical tests. The course is organized around the question of how to do good research. Topics to be covered include common threats to validity in research design, decisions regarding the choice of samples and settings, measurement issues such as reliability and validity, estimation methods, data collection tools, and ethics in planning, conduct, and publication of research. The seminar thus serves as a complement to other basic and advanced research method courses, and will develop skills needed to: 1. build and analyze theoretical arguments 2. design effective tests of theory 3. understand the interplay between theory building and theory testing Students will get some experience critiquing the methodology used in published studies and hopefully develop some idea about how to start conducting their own dissertation research.

 

MRES 609 Professional Development Seminar I or BAN 599 Graduate Seminar:

Professional Development Seminar I This is a weekly seminar (coordinated by a faculty member or a faculty team) that all doctoral students are expected to a attend and actively participate. The objectives are to orient the student to research traditions in sub-fields of management studies and to the professional life of an academic. With regard to the first objective students are exposed to current scholarly research through presentations by faculty members and invited speakers as well as the work and experiences of their doctoral colleagues. There are also sessions that specifically explore the current state of research in Turkey in particular areas of management studies. With regard to the academic profession there are opportunities to address issues related to developing publishable work, the review process, and refereeing as well as getting prepared for teaching responsibilities.

 

Graduate Seminar This seminar course provides a non-credit framework for the continuous monitoring and collegial discussion of MA students' thesis research and writing, which they are expected to accomplish under the supervision of a Faculty member from the relevant field.

 

GR 501M Academic Practices and Development:

Academic Practices and Development This course introduces fundamental principles in teaching and learning for graduate students in the event that they choose a career in academia.In addition, this course acculturates students to the practices and culture of Sabanci University. Through a series of workshops, graduate students will learn about best practices in teaching and learning, ethics, publication of research and how to apply them to the current student population at Sabanci University. Once students have participated in this series of workshops, they will help out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 502M Academic Practices and Development  2:

Academic Practices and Development 2 This course is a follow-up to GR 501M and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. This course will enable graduate students to reflect on their first semester helping out with a course, plan for the coming semester, and develop new skills in areas such a teaching with technology and grading. Through a series of workshops, graduate students will learn about best practices in teaching and learning, and how to apply them to the current student population at Sabanci University. Students will continue to helping out with one or more courses offered at the University, which will allow them to apply the principles learned in the workshop.

 

GR 555M Academic Writing for Graduate Students:

Academic Writing for Graduate Students This course aims to enhance the academic communication skills of graduate students with the goal of facilitating research output. To this aim, this course helps master’s and doctoral students develop skills essential for writing academic papers and theses in English. It provides guidelines on writing for the rhetorical genres characteristic of academic writing in the social sciences and humanities such as literature review, abstract, proposal, article for publication, and thesis. Students will also help out with one or more courses offered at the University.

 

GR 503M Academic Practices and Development  3:

Academic Practices and Development 3 This course is a follow-up to GR501M and GR502M, and aims to provide further opportunities for graduate students to develop their skills in teaching and learning in higher education. Students in this course will be observed by a supervisor or another observer at least once per semester in order to provide feedback on the student’s teaching performance as well as have the option to participate in additional professional development activities. Students will continue helping out with one or more courses offered at the University, which will allow them to apply the principles learned in this and previous courses.

 

Core Area Courses:

(For students having MS Degree)

ECON 501 Microeconomics I:

Microeconomics I Consumer and demand theory, production and theory of the firm; competitive markets, partial and general equilibrium theory.

 

ECON 502 Microeconomics II:

Microeconomics II Choice under uncertainty; basic game theory; imperfect competition, strategic interaction, entry; adverse selection, signalling, screening, moral hazard; mechanism mechanism design; general equilibrium under uncertainty; axiomatic and coalitional bargaining, cooperative models.

 

ECON 505 Quantitative Methods:

Quantitative Methods The course introduces students to research methods, analysis and design and aims to expose them to ethical considerations in research and publishing. Topics included are linear algebra; probability theory, random variables distributions, hypothesis testing, asymptotic distribution theory, estimation.

 

ECON 506 Econometrics:

Econometrics Classical linear regression model, generalized least squares generalized method of moments, qualitative dependent variable models, time series analysis.

 

Core Area Courses:

(For students having BS Degree)

 

ECON 501 Microeconomics I:

Microeconomics I Consumer and demand theory, production and theory of the firm; competitive markets, partial and general equilibrium theory.

 

ECON 502 Microeconomics II:

Microeconomics II Choice under uncertainty; basic game theory; imperfect competition, strategic interaction, entry; adverse selection, signalling, screening, moral hazard; mechanism mechanism design; general equilibrium under uncertainty; axiomatic and coalitional bargaining, cooperative models.

 

ECON 503 Macroeconomics I:

Macroeconomics I Traditional and endogenous growth theories real business cycles, overlapping generation models.

 

ECON 505 Quantitative Methods:

Quantitative Methods The course introduces students to research methods, analysis and design and aims to expose them to ethical considerations in research and publishing. Topics included are linear algebra; probability theory, random variables distributions, hypothesis testing, asymptotic distribution theory, estimation.

 

ECON 506 Econometrics:

Econometrics Classical linear regression model, generalized least squares generalized method of moments, qualitative dependent variable models, time series analysis.

 

FIN 621 PhD Seminar in Finance V: Research Paper I:

PhD Seminar in Finance V: Research Paper I In this course, doctoral students are expected to write a research proposal, conduct literature review, or replicate in part an existing research paper in the field. The course guides her/him through the various stages involved in formulating a research question, investigating existing literature on the topic, and executing preliminary scientific analysis. The course is aimed to be a first step in writing a dissertation proposal.

 

Elective Courses:

(For MS degree students, 15 credits and 5 courses , For BS degree students, 24 credits and 8 courses are required with advisor's approval)

Course CodeCourse NameSU Credit
ECON 503Macroeconomics I3
ECON 604Applied Econometrics3
FIN 611PhD Seminar in Finance I : Corporate3
FIN 618PhD Seminar in Finance II: Asset Pricing Theory3
FIN 619PhD Seminar in Finance III: Empirical Corporate Finance3
FIN 620PhD Seminar in Finance IV: Empirical Asset Pricing3
FIN 621PhD Seminar in Finance V: Research Paper I3
FIN 622PhD Seminar in Finance V: Research Paper II3
MFIN 501Principles of Finance1,5
MFIN 502Corporate Finance1,5
MFIN 510Financial Statement Analysis1,5
MFIN 511Portfolio Theory1,5
MFIN 512Fixed-Income Analytics1,5
MFIN 513Money & Banking 11,5
MFIN 516Financial Modeling -11,5
MFIN 520Valuation1,5
MFIN 522Derivative Securities1,5
MFIN 523Financial Risk Management1,5
MFIN 524Mergers, Acquisitions and Corporate Restructuring1,5
MFIN 535International Finance1,5
MFIN 599Wealth Management3

Ph.D. Requirements:

  • Students admitted with master's degree should complete the courses in maximum 4 semesters and the program should be completed in maximum 8 semesters.
  • Students admitted with bachelor's degree should complete the courses in maximum 6 semesters and the program should be completed in maximum 10 semesters.
  • If the Ph.D. students, admitted with master's degree who can not complete their thesis in 8 semesters, can take 4 additional semester. If the Ph.D. students, admitted with bachelor's degree who can not complete thesis in 10 semesters can take 4 additional semesters, too. These students must have been successful in PhD Qualifying Exam and their thesis proposal must have been accepted.
  • Ph.D. students majoring in one of the four main areas of specialization can complete their coursework in two years by fulfilling the course requirements indicated below.

WITH MS DEGREE

 Course NumberSU CreditECTS
Required Courses6341
Core Area Courses41240
Elective Courses51530
Total1530111

WITH BS DEGREE

 Course NumberSU CreditECTS
Required Courses6341
Core Area Courses61854
Elective Courses82455
Total2045150

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