A successful Ph.D. in Information Systems is both a philosopher and scholar who studies and contributes to systems of beliefs about how Information Systems operate and how they affect the various constituencies that use them.
They are naturally curious about how such systems operate, how they are used, and how to make them better in terms of productivity, usability, and interoperability. The primary goal of any Ph.D. program is to help students learn to think like a scholar - to ask interesting questions and to systematically answer them. The Ph.D. program in Information Systems at University of Kansas is an apprenticeship toward entry into the community of scholars who create and disseminate fundamental knowledge in IS. Upon successful completion of the program, the new Ph.D. will be capable of independent research and teaching, and be poised to join the global community of science.
While successful candidates for admission are expected to have a background with information systems and an understanding of the fundamental concepts in system development, database and networking, applicants without such background will be considered provided they agree to additional coursework as part of their doctoral program. Such students will be required to take additional courses at the Masters level to ensure that they have a solid knowledge of information systems. We look for three characteristics in our applicants: i) a good student as demonstrated by prior degrees, GPA, and GMAT (or GRE) scores; ii) some professional experience with information systems; c) some academic experience in teaching and/or research. Not all of our current students have all three characteristics, because we are looking for people we believe are most likely to succeed, rather than following a fixed formula. Some have very eclectic backgrounds. The program is full-time and no part-time program is available.
1. DSCI 920: Probability for Business Research (or an equivalent course)
2. DSCI 921: Statistics for Business Research (or an equivalent course)
3. BE 917: Advanced Managerial Economics (or an equivalent course)
OR ECON 700: Microeconomics Theory
4. MGMT 954: Individual and Interactionist Perspectives of Organizations**
5. MGMT 916: Seminar in Organization Theory or another course in OB or Psychology
approved by the AIS faculty
6. MGMT 905: Philosophy of the Behavioral and Organizational Sciences
Area of Concentration
7. IST 995: Introduction to Behavioral Research in Information Systems
8. IST 995: Research Seminar on Systems Analysis and Design
9. IST 995: Research Seminar on Organizational Impacts of IS/IT
10. IST 995: Research Seminar on Database and Advanced Technologies
11. IST 995: Research Seminar on Decision Support Systems and Collaborative Technologies
Coursework in the area of concentration is supplemented and strengthened by study in one or two supporting areas. A supporting area is one that supplements and complements the area of concentration. The aspirant will satisfy the supporting area requirement by taking at least four advanced courses in the supporting areas (at least two courses in each of two supporting areas, or at least four courses in one supporting area). Courses recommended for preparation for the qualifiers may not be included in satisfying the supporting area
Program Requirements and Information
Area of Concentration
Most students admitted in information systems typically will select that area as their concentration. However, an aspirant, with the assistance of his or her faculty advisor and the area faculty, may propose an interdisciplinary area of concentration. The aspirant must take at least five advanced courses in the area of concentration. These courses may include those offered outside the School of Business.
Coursework in the area of concentration is supplemented and strengthened by study in one or two supporting areas. A supporting area is one that supplements and complements the area of concentration. The aspirant will satisfy the supporting area requirement by taking at least four advanced courses in the supporting areas (at least two courses in each of two supporting areas, or at least four courses in one supporting area). The typical supporting areas for decision science students are marketing, economics, finance, etc. Courses recommended for preparation for the qualifiers may not be included in satisfying the supporting area requirement.
For successful qualifier assessment, the student’s program of study should include adequate preparation in research methodology. A sound research is always grounded on sound methodology. A doctoral student in decision science has the opportunity to develop methodological skill in probability and statistics, optimization, uncertain reasoning, game theory, and econometrics. A typical doctoral dissertation often utilizes one or more of the following research methodology: empirical, analytical, behavioral, and computational.
Degree Completion Timeline
Years 1-2: Coursework* Year 3: Comprehensive Exams Year 4: Dissertation Proposal Year 5: Dissertation Defense (Some students can complete the program in four years.)
Over the past several years, our PhD graduates have been placed at schools such as University of Vermont, Michigan Technological University, University of Arkansas.