The Ph.D. in Information Systems is primarily designed to prepare students for an academic career, involving research and teaching, at leading Universities around the world. Through a combination of coursework, research seminars, and mentored research, students acquire breadth of knowledge in the range of issues that define the field of IS, as well as in-depth expertise in an area of their choice.

The IS Department faculty have a wide range of research interests, including electronic commerce, data warehousing, data modeling, knowledge management, management of the IS function, electronic social networks, business intelligence, and the role of IT in organization design and strategy. They regularly publish in leading journals in the field such as MIS Quarterly, Information Systems Research, Journal of MIS, ACM Transactions on Database Systems, VLDB journal, and others. Our faculty also serve in editorial roles on many of these journals. Finally, alliances with many leading vendors such as Microsoft, Dell, IBM, and SAP mean that our students always have access to the latest technologies for both their research and teaching needs.

Program Structure

The degree requires 121-141 graduate credits. The last 45 credits, exclusive of research credits, must be completed at the University of Cincinnati or under its direction. These credit hours will be distributed as follows:

* Students with an MBA should already have this

Note:Some students may be asked to take a few graduate level IS courses in 
         addition to the above coursework depending on background.

Program Components Introductory Doctoral Seminar: Introduction to Research and Teaching

This seminar will focus on the key issues and topics of the profession, the role of writing in research and publishing, and an introduction to and experience in successful teaching. It will also introduce new doctoral students to the portfolio of research being conducted by faculty and graduate students, and to research resources available at UC.

Core Statistics Requirement

Students must take the following two statistics courses

22QA721 Methods of Statistics 4 credits
A survey of statistical methodologies useful for research in a variety of disciplines. Estimation, significance testing, regression, ANOVA and computer applications. Recent syllabus .

22QA722 Regression Analysis 4 credits
Estimation and inference making using regression models; method of least squares, formal methods of inference, model diagnostics based on analysis of residuals, use of dummy variables, variable selection and model building. Introduction to logistic models. Prereq.: 22QA721.

Research Methods

Each student is required to take the following course.

22QA726 Design of Experiments 4 credits
Basic concepts of experimental design. Linear statistical models; analysis of variance and estimation for completely randomized and various blocked designs; analysis of covariance; analysis of unbalanced data; random and mixed models; repeated measures, split-plot, and nested designs, Prerequisite: 22QA722.

In addition, students must take 2 additional methodological courses. Typically, we would expect students to choose from among the following courses. However, substitute courses may be acceptable – these should be discussed by the student with department Ph.D. advisor.

22QA723 Sample Survey 4 credits
Statistical aspects of sample survey. Survey designs; simple random, stratified, cluster, multi-stage, and probability proportional to size sampling. Estimation methods for means, totals, ratios, and proportions. Planning and implementing surveys. Prereq.: 22QA721.

22QA724 Multivariate Methods 4 credits
Multivariate normal distribution, its parameters and model diagnostics. Statistical analyses involving multivariate means, covariance and correlation matrices; Special multivariate techniques; principle components, canonical, discriminant, and factor analyses. Prerequisites: 22QA722; 22QA731 suggested but not required.

22QA727 Data Mining 4 credits
Hands-on data analysis experiences on real world data with varying topics from year to year using major statistical software, such as SAS and Splus. Case studies involving data management and model fitting; model interpretation and diagnostics. Model approaches including exploratory data analysis; linear models; generalized linear models; classification and regression trees; kernel, splines, and additive models. Prereq.: 22QA722.

22MKTG887 Advanced Measurement and Analysis Methods 4 credits
Treatment of measurement techniques, scaling methods, and other analytical procedures applicable to marketing research. Prereq.: Perm. of instructor

Philosophy of Science

All doctoral students will take a course in philosophy of science, most likely in the first or second year of doctoral study.

Business Core/Electives

Students without MBA degrees will be required to take 20 credit hours from the MBA core. The specific courses will be drawn from across the business disciplines and will be selected in consultation with the department Ph.D. Advisor.

Area of Concentration

All students will be required to take the following 6 seminars in IS:

Theoretical Foundations for IS Research
This seminar will introduce key theoretical perspectives from various reference disciplines (e.g., management, economics, computer science, psychology, and sociology) that are widely used in IS research. It will include illustrative works from IS literature that draw on these theoretical disciplines.

Technical Foundations for IS Research
Research on technical subjects in IS uses a very different paradigm than the more behaviorally oriented research that will be the focus of the previous seminar. This seminar will familiarize students with this alternative paradigm and introduce them to research on technical topics in IS such as data modeling, software engineering, IT architecture, artificial intelligence applications, etc.

Research on IS Development and Management
This seminar will cover research on the design, deployment, and use of the IT artifact -- e.g., information systems (IS) development methodologies, control and coordination of IS projects, and implementation approaches. It will also include topics on the management of the IS function, e.g., IS Leadership, Design of the IS Organization, and Outsourcing.

Research on Organizational Impacts of IS
This course will focus on the role of IS in shaping organizational design and strategy, including such topics as ERP systems, inter-organizational information systems, supply chain management, knowledge management, and electronic commerce.

Special Topics in IS Research
This seminar will explore research on contemporary issues in IS.

IS Colloquium
Student will participate in the monthly IS research presentation series for the first 2 years of the program. They will be required to submit a written analysis of each presentation.

Support Area

All students will be required to take a minimum of 16 advanced credit hours in an area related to, but different from IS. Courses may be selected from any discipline or combination of disciplines within the University, with the approval of the department Ph.D. Advisor. Typical support areas will be Management, Accounting. Marketing, Psychology/Sociology, or Computer Science (for students more interested in technical areas of research).

Area-specified course hours

Students will be required to take 8 credit hours in an area designed to meet individual interests and career objectives. Courses in this category may be additional hours in IS, in the support area, research design and methodology, or others. This will be decided in consultation with the department Ph.D. Advisor.

Program of Study for PhD in Information Systems

The following is a sample program of study for a student.