The management science and systems discipline in the Management PhD program prepares students to become leading researchers and teachers at top universities or executive-level decision makers in industry. Each student follows a slightly different path, depending on research interests, allowing some flexibility to the curriculum.
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
This seminar is a doctoral seminar for doctoral students majoring or minoring in the information systems area.
Credits: 3
Semesters offered:
The course begins with a discussion on `What is research?¿ and the distinct research methods used in the information systems area. The course then moves to a discussing frameworks that provide guidelines relating to Design Science Research.
Credits: 3
Semesters offered:
Doctoral seminar in the field of information assurance.
Credits: 3
Semesters offered:
Credits: variable
Semesters offered:
(Fall: must register for two consecutive years)
One objective of the seminar is to acquaint participants with the research approaches and procedures used in management systems and to encourage them to formulate research proposals suitable for dissertation purposes. The course also addresses fundamental concepts about the role, use, construction and evaluation of theories and theoretical models.
Credits: variable
Semesters offered: Fall 2024 | Spring 2024
Fall 2024 (08/26/2024 - 12/09/2024)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11436 | F4S | TUT | ARR | Arr Arr | Sharman, Raj | ||
| 11321 | F5S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy | ||
| 11349 | F2S | TUT | ARR | Arr Arr | Tang, Shaojie | ||
| 11404 | F3S | TUT | ARR | Arr Arr | Unknown | ||
| 11433 | F1S | TUT | F | 9 - 11:50 a.m. | Jacobs 325B | Sanders, George L. | |
| 11362 | F7S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 11334 | F6S | TUT | ARR | Arr Arr | Unknown |
Spring 2024 (01/24/2024 - 05/07/2024)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 11042 | S3S | TUT | ARR | Arr Arr | Ramesh, Ramaswamy | ||
| 11134 | S1S | TUT | ARR | Arr Arr | Suresh, Nallan Chakravarthy | ||
| 11111 | S2S | TUT | ARR | Arr Arr | Smith, Sanjukta Das | ||
| 11053 | 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
Semesters offered: Fall 2024 | Spring 2024
Fall 2024 (08/26/2024 - 12/09/2024)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 19771 | F2S | LEC | TR | 8 - 9:20 a.m. | Jacobs 110 | Gaia, Joana | |
| 17091 | F1S | LEC | TR | 2 - 3:20 p.m. | Jacobs 110 | Gaia, Joana |
Spring 2024 (01/24/2024 - 05/07/2024)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 21976 | S4S | LEC | MW | 11 a.m. - 12:20 p.m. | Jacobs 122 | Sellitto, Dominic Michael | |
| 20399 | S3S | LEC | TR | 11 a.m. - 12:20 p.m. | Frnczk 422 | Gaia, Joana | |
| 22886 | ABO1 | LEC | UNKWN | Remote | Hunt, Kyle Jeffrey | ||
| 16408 | S1S | LEC | MW | 11 a.m. - 12:20 p.m. | Alfier 102 | Kraude, Richard Leland | |
| 19513 | S2S | LEC | MW | 12:30 - 1:50 p.m. | Alfier 102 | Kraude, Richard Leland |
IE 573 Discrete Optimization
IE 575 Stochastic Methods
IE 551 Simulation and Stochastic Models
IE 675 Game Theory
Students will learn contemporary terms, philosophies, technologies, controls and strategies that go into buttressing an organization¿s informational, data-driven, well-being. Students will gain experience assess the growing number of cyber risks to our organizational assets, and how to treat these risks by prioritizing and arraying resources. Common information security controls (both technical and programmatic) will be covered, guided by an analysis of the leading information and cyber security control frameworks such as ISO 27000, NIST CSF, and the CIS top 18 security controls. Students will learn about strategic level security program implementation including, policy management, governance, return on investment and compliance whilst continually improving risk exposure. Cybersecurity is one part of the cross-functional milieu that this class will examine. Multidisciplinary topics that intersect with security program implementation will include Technical, Managerial, Executive, Finance, Human Resources, Business Continuity, Strategic IT Management, Legal, Psychological, Audit, Compliance and Control partnerships. Various IT hosting strategies including on-premises and cloud classifications will be examined for their security merits, challenges and risk exposures. Emerging impactful topics such as new/changing regulation and growth of generative artificial intelligence will be examined in terms of their implications on the information security industry and the deployment of future-proof protections.
Credits: 3
Semesters offered:
Pre-Requisite: MGS 602 and MGS 605 or MIS student
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
Semesters offered: Spring 2024
Spring 2024 (01/24/2024 - 05/07/2024)
| Reg. Num. | Section | Type | Topic | Days | Time | Location | Instructor |
| 21763 | S2S | LEC | MW | 3:30 - 4:50 p.m. | Alfier 102 | Lindsey, Charles Daniel | |
| 11139 | S1S | LEC | R | 6:30 - 9:10 p.m. | Alfier 104 | Miles, Stephen |
** Courses satisfying statistics and methodology requirements.
If you are a doctoral student outside of the School of Management who is interested in obtaining an external area of focus in Management Science and Systems, you should consult with your academic advisor. Course requirements are:
Refer to the PhD Handbook for complete information on: