The Management Science and Systems major has two tracks. The Management Science track covers the areas of mathematical programming, multi-criteria decision-making, design science, behavioral science, statistical methodology and application, and decision support systems. The track emphasizes the use of mathematical, statistical and economic techniques to model complex management and management-related problems.
The Management Systems track covers the areas of management information systems, design science, behavioral science, decision support systems, information assurance, e-commerce and global information technology management. The concentration emphasizes the use of systems analysis techniques, quantitative techniques, simulation, model and theory building, statistical analysis, and other analytic methods in the structuring and resolution of management problems related to the development, use, and impacts of information technology and information systems in organizational, individual and societal domains.
The tracks have the following concentrations:
A. Management Science Track
1. Mathematical Programming and Decision Making
2. Statistical Methods and Applications (including Forecasting)
B. Management Systems Track
1. Information Assurance
2. Management Information Systems
3. Global IT Management
You must develop or have competence in accounting, economics, finance, marketing, organizational behavior/organizational theory and strategic management equivalent to one first-year MBA course in each area before graduating from the PhD program.
ECON 613** Introduction to Econometrics
ECON 614** Econometric Applications and Methods
IE 576** Applied Stochastic Processes
MGQ 614 Advanced Probability and Statistics or IE575
MGQ 616 Stochastic Models of Management Science or IE 572
MGS 786 Design Science
Credits: 3.00
Semesters offered:
Credits: 3.00
Semesters offered:
(Fall: must register for two consecutive years)
Credits: variable
Semesters offered: Fall 2022 | Spring 2022
Fall 2022 (08/29/2022 - 12/09/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11710 | F1S | TUT | F | 9 - 11:50 a.m. | Jacobs 325B | Sanders, George L. | |
| 11714 | F4S | TUT | ARR | Arr Arr | Sharman, Raj | ||
| 11621 | F7S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 11603 | F2S | TUT | ARR | Arr Arr | Unknown | ||
| 11579 | F6S | TUT | ARR | Arr Arr | Unknown | ||
| 11673 | F3S | TUT | ARR | Arr Arr | Unknown | ||
| 11563 | F5S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy |
Spring 2022 (01/31/2022 - 05/13/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11219 | S3S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy | ||
| 11370 | S1S | TUT | ARR | Arr Arr | Suresh, Nallan Chakravarthy | ||
| 11238 | S5S | TUT | ARR | Arr Arr | Sanders, George L. | ||
| 11337 | S2S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 11235 | S4S | TUT | ARR | Arr Arr | Sharman, Raj |
(Spring: must register for two consecutive years)
This course teaches the technical and managerial skills needed in developing predictive analytics applications which are used by customer-centric corporations - retail, financial, communication, and marketing groups - to help make decisions involving complex systems. The course concentrates on a set of well-known predictive analytics methods to support business decision making. Topics such as association rule mining, decision trees, neural networks, regression analysis and cluster analysis are covered in great depth. Extensive hands-on experience using software such as SAS Enterprise Miner is provided.
Credits: 3.00
Semesters offered: Fall 2022 | Spring 2022
Fall 2022 (08/29/2022 - 12/09/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 24390 | F3S | LEC | TR | 2 - 3:20 p.m. | Jacobs 106 | Hunt, Kyle Jeffrey | |
| 18437 | F1S | LEC | TR | 2 - 3:20 p.m. | Jacobs 110 | Smith, Sanjukta Das | |
| 21849 | F2S | LEC | TR | 12:30 - 1:50 p.m. | Jacobs 122 | Hunt, Kyle Jeffrey |
Spring 2022 (01/31/2022 - 05/13/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 23905 | S3S | LEC | MW | 12:30 - 1:50 p.m. | Jacobs 122 | Smith, Sanjukta Das | |
| 22313 | S2S | LEC | MW | 12:30 - 1:50 p.m. | Alfier 102 | Gaia, Joana | |
| 17918 | S1S | LEC | MW | 11 a.m. - 12:20 p.m. | Alfier 102 | Gaia, Joana |
IE 573 Discrete Optimization
IE 575 Stochastic Methods
IE 551 Simulation and Stochastic Models
IE 675 Game Theory
This is an interdisciplinary course in Information Assurance that has two primary objectives: 1) to introduce students to fundamental concepts, terminologies, IA models and practices. 2) to view how different fields of disciplines interact in this area. The course will familiarize students with the technical, legal, socio-political, and managerial issues of IA. Broadly, the issues that we will cover in this course include: security investigation and analysis; ethical, legal, and professional aspects of Information assurance; risk management and implementation and maintenance of information assurance.
Credits: 3.00
Semesters offered: Fall 2022
Pre-Requisite: MGS 602 or MIS student.
Fall 2022 (08/29/2022 - 12/09/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 16132 | F2S | LEC | MW | 12:30 - 1:50 p.m. | Obrian 210 | Cleary, Kevin Patrick | |
| 21854 | F1S | LEC | TR | 5 - 6:20 p.m. | Knox 14 | Cleary, Kevin Patrick |
The main objective of this course is to introduce students to the theory and practice of doing business via the Internet. Topics include: elements of the infrastructure of electronic commerce; technologies and applications in electronic commerce; using electronic commerce for the creation of competitive advantages; planning technology-based strategies to achieve business goals. The course will rely heavily on research and peer learning with the instructor serving as catalyst, facilitator, and evaluator in a collaborative environment.
Credits: 3.00
Semesters offered: Spring 2022
Spring 2022 (01/31/2022 - 05/13/2022)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11375 | S1S | LEC | R | 6:30 - 9:10 p.m. | Frnczk 422 | Miles, Stephen |
