Program Summary

Quantitative Methods involves topics in both applied optimization and applied statistics. Applied optimization explores resource allocation issues that frequently arise in managerial decision making. In an era of dwindling resources and increasing competition, optimization questions have assumed a new and urgent importance. Doctoral seminars focus on advanced optimization applications and methodologies. Related courses are available from areas such as industrial and electrical engineering and computer sciences. Faculty collaboration with other areas of management and related engineering programs enables students to participate in research on a stimulating range of optimization applications. Current areas of faculty interest in applied optimization include transportation, communication, distribution, and manufacturing systems. Other application domains include auditing, scheduling and quality control.

Applied statistics addresses managerial problems in which randomness or uncertainty complicates the decision environment. This specialization emphasizes in-depth study of the relevant methodology with the flexibility to apply these methods to any areas of management. Courses from departments such as economics, statistics, and industrial engineering as well as other areas of management offer the student a rich variety of topics for applied statistics research. Current faculty research interests in applied statistics include stochastic marketing models, auditing and acceptance sampling, statistical decision theory, decision analysis, and quality control.

Probabilistic and deterministic mathematical models for solving management problems are the focus of the quantitative methods/marketing science Ph.D. option. This option requires basic proficiency in probability theory, mathematical statistics, decision analysis, and mathematical programming. Advanced seminars explore selected research topics concerning quantitative methods applications to management problems. The plan of study may include mathematics, statistics, computer science and Management Information Systems , industrial engineering and Economics courses.

Unique Features

• Faculty on Editorial Boards for top academic journals.
• Doctoral fellowships available
• Quantitative research receives special emphasis in program of study
• Small program with low student-faculty ratio

Student Profile (what we look for in an applicant)

• Strong analytical background.
• MBA is helpful, but not required; graduate degree a plus.
• Work experience not required, although applicants typically have some experience in strategy, consulting, or a technical field such as engineering.

Plan of Study

Students are required to submit a formal plan of study to the Graduate School by the end of the Spring Semester of their second year in the doctoral program, and prior to taking the preliminary examination.

Doctoral Dissertation Proposal/Dissertation Committee Requirement

Within twelve months after passing the preliminary examination, each student must formally present and defend a dissertation research proposal to his/her dissertation committee. To be accepted, the proposal must represent substantial progress towards completion of a doctoral thesis along with a statement of further work to be performed. Once accepted by the committee, the proposal is considered a "contract" that will guide the student towards completion of the dissertation. A student may be dropped from the program if there is a significant delay in achieving an acceptable proposal.

Defense of Dissertation

Each student is required to make a public defense of his/her dissertation. The required procedures for holding a dissertation defense are listed in the revised Ph.D. Program in Management.

Faculty & Research Interests

Arnab Bisi inventory control, stochastic modeling, supply chain management, and production planning

Patrick Johanns quantitative analysis, management science, operations management, business forecasting

Yanjun Li operations research, integer programming, combinatorial optimization, networks and graph, location and distribution, vehicle routing and transportation, lot sizing and scheduling, set covering and packing problems, maintenance contracts

Robert D. Plante development of state-of-the-art statistical quality control and improvement models and procedures for contemporary and futuristic manufacturing systems

Padmapriya Rajagopalan health economics, medical sociology, public finance, labor economics, applied economics, economic development

Jen Tang applied statistics and quality control, distribution theory of statistical multivariate analysis

Kwei Tang on-line process control, integration of quality functions in a manufacturing organization, e-commerce, and data mining

Mohit Tawarmalani mathematical programming, optimization, complexity and approximation, symbolic computing (on sabbatical)

Hui Zhao managing service parts logistics and investigating decentralized supply chains with inventory flexibility (e.g. inventory pooling) using game theoretic approach

Recent Graduates
(First/Last Name, year of graduation, dissertation title, placement)

Ping H. Huang, 2008, New Results on Knapsack Problems, Purdue University.

John Norris, 2007, Essays on Operational Efficiency in Service Operations: Applications in Health Care, Unavailable.

Zhefang Zhou, 2006, Dynamic Pricing and Warranty Policies for Products with Fixed Lifetime, City University of Hong Kong.

Binling Lu, 2004, Coordination Strategies for Products with a Short Life Cycle in a Capacitated Channel.

Hakan Tarakci, 2004, Coordination in Maintenance Outsourcing, Melbourne Business School.

Fu-Shiang Tseng, 2004, Designs of Maintenance Outsourcing Contracts. Yuan-Ze University - Taiwan.

Wei Xu, 2003, Behavioral Bias Driven Trading and Return Momentum. Law and Economics Consulting Group (LECG).

Haelim Seo, 2003, Learning Assessment and Depreciation in Learning. Korean Airforce.