The department has recently revamped the core requirement for its PhD program. From academic year 2008/09, the required coursework will comprise 10 compulsory half-modules (equivalent to 5 full modules) and 5 electives. In addition, NUS Business School has a basic business knowledge requirement for all its PhD students to take two MBA modules.
Students will take these 10 half-modules in a pre-determined sequence during their first two semesters in the program.
BDC5111 Linear Programming
BDC5113 Convex Optimization
BDC5115 Discrete Optimization and Applications
BDC5121 Stochastic Models
BDC5123 Simulation Modeling & Analysis
BDC5131 Management of Information
BDC6111 Inventory Management
BDC6113 Supply Chain Management
BDC6121 Operations Management
BDC6123 Operations & Process Design
Note:
Students may be required by their supervisors to take more than the minimum 10 courses if necessary before taking the preliminary exams and proceeding to the dissertation stage. When selecting elective courses, students are required to consult their individual mentor/supervisor or relevant departmental authorities, e.g., Department PhD Committee Chairman, if no mentor/supervisor has been appointed.
Students will be allowed to take elective courses from among the many PhD level courses that are offered each year by various academic units in NUS. In addition to elective courses offered by the Department of Decision Sciences and other departments in NUS Business School, students make take also take courses from (for example) Department of Mathematics, Department of Statistics & Applied Probability, Department of Systems and Industrial Engineering, Department of Economics, Department of Psychology, and School of Computing.
NUS Business School requires its PhD students who do not have background in business studies to take two MBA courses to help them gain a broader perspective on business. (The requirement for these MBA courses is waived if a student has had an undergraduate degree in business or if he/she provides proof that similar courses have been taken before the start of his/her Ph.D studies.)
PhD students from the Department of Decision Sciences will take two courses from the following list of MBA courses:
• BMA 5001 Managerial Economics (no prereq)
• BMA 5003 Financial Accounting (no prereq)
• BMA 5008 Financial Management (need BMA5003 or concurrent enrolment)
• BMA 5009 Marketing Management (no prereq)
• BMA 5112 Asia Pacific Business (no prereq)
• BMA 5013 Corporate Strategy (need BMA5003)
Note:
Students have to pass these MBA courses before taking their preliminary exams. Grades from these courses will be included in the computation of the student's grade point average.
Students are required to take 3-4 courses per semester (including core, elective and MBA courses). Students are expected to finish their courses in three semesters and take the preliminary exam after three semesters.
Each student is also required to provide research/teaching assistance to a faculty member (normally the mentor/supervisor) of about 6 hours per week. Students are allowed to negotiate for a lighter assistance work load during exam periods but may be required to make up in subsequent periods for lost time.
The School requires all students to take two seminar courses. This requirement is not part of the coursework requirement described earlier. These compulsory seminars will be spread over two semesters: BRP6551 and BRP6552, which will run over two regular semesters of each academic year. The two modules can be taken any time during the program. Students are expected to enrol for these two modules at some point during the program, preferably before the qualifying examination. All students are expected to take this module. During the modules, each student is expected to present a paper at least once. Each seminar module is worth 2 module credits. Students will be evaluated based on their attendance, participation, and contribution in the seminars. A satisfactory/unsatisfactory grade will be given. All students must obtain a satisfactory grade for both modules to graduate.
In addition, students are encouraged to participate in research seminars even after fulfilling these two module requirements.
Modules Offered by the Decision Sciences Department
Core Modules
BDC5111 Linear Programming (Half Module)
Linear Programming (LP) involves the optimization of a linear objective function, subject to linear equality and inequality constraints. It is arguably the most important optimization model, which has been extensively applied in business, economic situations and engineered systems. We will cover some main applications of LP, duality and geometry, as well as the core algorithms for LP. Imbue PhD students with the fundamental theory and modeling power of Linear Programming (LP). The knowledge of LP is precursor to many advance optimization courses such as Discrete Optimization and Applications and Convex Optimization.
BDC5113 Convex Optimization (Half Module)
Convex optimization is one of the most important models in management sciences. It is also a basis for further study in optimization, both in theory and in computation. This module will provide such a basis, while put enough attention on business applications. The objective is to introduce the fundamental ideas and concepts in convex optimization to PhD students. Focus will be on theory and analysis of algorithm for problems in this area.
BDC5115 Discrete Optimization and Applications (Half Module)
Discrete optimization is the study of problems where the goal is to find an optimal arrangement from among a finite set of possible arrangements. Many applications in business, industry, and computer science lead to such problems, and we will touch on the theory behind these applications. We cover several important concepts and applications in this area. Topics covered include: (1) Matroid and Greedy Algorithm; (2) Network Flow; (3) Matching; (4) Polyhedral Methods, including Cutting Plane and Column Generation; (5) Sub-modular minimization. We discuss how these approaches can be used to tackle problems arising in operations and other diverse areas.
BDC5121 Stochastic Models (Half Module)
The primary objective of the module is to provide graduate students with basic knowledge on probability models and stochastic processes in operations research and management science.
The topics include discrete-time and continuous-time Markov chains, Poisson processes, birth and death processes, renewal reward processes, and regenerative processes. The module is to equip the students with sufficient background knowledge on stochastic operations research models so as to enable them to 1) understand related literature in the field of management science and engineering management; and 2) to conduct PhD level research on business application problems involving randomness and stochastics.
BDC5123 Simulation Modeling and Analysis (Half Module)
The course introduces students to fundamental simulation theories, modeling and analysis skills. The course covers building valid and credible models, random-number generator and random-variate generation, modeling and design of experiment, and analysis of simulation output. The primary attention will be given to modeling problems in business, service operations and supply chain systems, by means of discrete-event simulation. Using spreadsheets and simulation software to build simulation models, conduct experiments and data analysis is essential in this course.
BDC5131 Management of Information (Half Module)
This module covers various concepts relating to key information technology in organizations and their use in operations and supply chain management. Topics covered include customer relationship management, knowledge management, electronic procurement, electronic business, interorganizational systems, and enterprise systems. The module is taught seminar style and based on a set of readings. Students will be equipped with knowledge about key information systems used in business operations. At the end of course, students will be better appreciate how information can be used in various parts of the value chain in business operations. As well, students will be better able to appreciate the use of information systems in different functional areas of business.
BDC6111 Inventory Management (Half Module)
This course will provide an in-depth study of a variety of production and inventory control planning problems, the development of mathematical models corresponding to these problems, and approaches for finding solutions. We will cover both classical deterministic and stochastic inventory models. In addition, we will discuss the recent trend in inventory management, such as the joint inventory and pricing decision and risk averse inventory models. Although many of the topics we will cover are of great interest to managers, our focus will be not on practice but on theory.
BDC6113 Supply Chain Management (Half Module)
The objective of this course is to expose students to the issues that need to be considered in designing and operating supply chains. We will start with an introduction to supply chain management including definition of supply chain management, key supply chain costs and metrics, and fundamental issues and trade-offs in supply chain management. We will then discuss the interactions between stages in a supply chain, double marginalization and contracts for supply chain coordination, strategic alliances and incentive alignment, channels of distribution, coordinating distribution strategies, pricing/promotions. We will also discuss how to explore good flexibility structure and the impact of flexibility in supply chain management.
BDC6121 Operations Management (Half Module)
We cover the following topics in Operations Management not already included in the other OMrelated modules: Operations Strategy, Service Operations, New Product Development and Project Management. We aim to provide an overview of the relevant literature as well as expose the students to the new developments and readings in these topics.
BDC6123 Operations and Process Design (Half Module)
The course objective is to introduce students to the research issues associated with key programs and initiatives undertaken by organizations to improve their operational capabilities and performance. Hence, this module focuses on the design, implementation and management of operations processes and systems. These processes and systems include programs and initiatives adopted by organizations to improve its operational and logistical performance. Topics covered include lean management, six sigma, TQM, enterprise resource planning (ERP), JIT, business process re-engineering (BPR), and knowledge management systems. The module follows a seminar-cum-discussion format.
Elective Modules
BDC5201 Multivariate Business Analytics
The module is designed to prepare students particularly for rigorous Business Research through a systematic study of multivariate analytics applicable to Business Intelligence and other enterprise areas. Topics include hands-on applications of multivariate regression & analysis of covariance, classification, clustering, principal components & factor analysis, multiple discriminant analysis, conjoint analysis, multidimensional scaling, and structural equation modeling. Data analyses to fields like finance, marketing and operations will be emphasized. Two key objectives are to understand the problems and solutions relating to management problems with multi-dimensional data and to effectively use computer software to analyze complex business data.
BDC6101 Seminar in Operations Management and Logistics
The objective this module is to expose students to the issues that need to be considered in designing and operating supply chains, and a variety of modeling tools available for their analysis. The readings will include literature on models for supply chain and logistics issues which offer insights into the management of supply chain activities, and/or present novel and applicable algorithmic ideas for new supply chain models.
BDC6102 Management Science Practicum
The goal of the module is to expose students to real life MS and logistics problems and provide the opportunity to study and solve such problems in an industrial setting. The students will study the problem in-depth, undertake novel/practical approaches to the problem drawing upon their coursework in the program as well as their own independent study, and apply their approach.
BDC6301 Current Issues in Information Systems and e-Business
This module examines current issues and trends in information systems and e-Business. Topics covered include strategic use of information technology (IT), information systems planning, knowledge management, impact of IT and e-Business, systems development and evaluation of information systems. Students will be required to critically analyze the theories and supporting research relating to these various issues. The issues will also be linked to various research areas that students can examine for their thesis.
BDC6400 Selected Topics in Decision Sciences
To provide candidates with an opportunity for study of selected advanced topics in particular fields such as BDC6400A Selected Topics in Decision Sciences – Robust Optimization. Topics to be announced.
BDC6500 Independent Study
The supervisor and student will determine an appropriate set of readings that will largely form the basis of the student’s thesis/dissertation. The supervisor will schedule regular meetings with the student to ensure that readings are up-to-date and well-understood. A term paper is required.