The David Eccles School of Business at the University of Utah offers a program of study leading to the Ph.D. in Business Administration with a major field in Information Systems. The Ph.D. program is a full-time program that typically requires a minimum of four years of study. The program curriculum prepares doctoral students to perform independent research in data-driven business analytics, artificial intelligence, information technology for healthcare, social media, and network analysis, and behavioral and economic impacts at individual and organizational levels. Information Systems PhD Coordinator: Paul Hu

Each student’s program of study is tailored to the student’s needs and interests. Students work with their department Ph.D. Committee or Supervisory Committee Chair to design their program of study. Below is an illustrative list of classes that might be used to compose a program of study.

A minimum of 15 major fields, 9 allied fields, and 15 research competency credit hours are required. Three credit hours in research must be a Philosophy of Science course. Students are also required to take an effective teaching course, which is held the week between the spring and summer semesters of their first year. Once students have completed all the necessary requirements to advance to candidacy, they are then required to complete a minimum of 14 hours of thesis research.

To learn more about each course, read the course descriptions in the General Catalog and Class Schedules.

Program Highlights

Faculty ranks in the
top 25 in the world

Seminar series with top researchers from around the world

Collegial supportive

Winter Finance

Work with
world-renowned researchers

Network with renowned scholars at Utah-BYU Winter Strategy Conference

Typical Program of Study

  • IS 6420: Database Theory & Design
  • IS 6480: Data Warehousing
  • IS 6482: Data Mining
  • OIS 7720: Special Topics: Operations Management
  • IS 7910: Special Study for PhD
  • Business Intelligence
  • IS Seminar: Empirical
  • IS Seminar: Technical
  • IS Seminar: Overview
  • CS 6350: Machine Learning
  • CS 6340: Natural Language Processing
  • CS 6150: Advanced Algorithms
  • MGT 7600: Seminar: Strategic Management Theory
  • MGT 7620: Seminar: Special Topics in Strategic Management
  • MGT 7800: Seminar: Research Foundations in Organizational Behavior
  • MGT 7820: Seminar: Organizational Theory
  • MGT 7910: Grad Special Study: PhD
  • MKTG 7570: Public Policy Issues in Marketing
  • MKTG 7700: Strategic Marketing
  • MKTG 7740: Marketing Models I
  • MKTG 7740: Marketing Models II
  • MKTG 7800: Seminar on Consumer Judgment and Decisions Making
  • MKTG 7810: Consumer Behavior Research in Marketing
  • PSY 6500: Quantitative Methods I
  • PSY 6510: Quantitative Methods II
  • PSY 6550: Structural Equation Modeling
  • MATH 6805: Introduction to Probability
  • MATH 6810: Stochastic Process and Simulation
  • MATH 6815: Stochastic Process and Simulation II
  • MGT 7100: Management Research Design
  • MGT 7200: Cross-Discipline Seminar
  • MGT 7300: Effective Teaching

Ideal Candidates