Information Systems Major

The Information Systems PhD program at the Robert H Smith School of Business is one of the best in the country and has been consistently ranked among the top 5 - 10 programs worldwide by US News and World Report, Business Week, and a number of other publications.

The UTD Top 100 World Rankings of Business Schools ranks the Robert H Smith School of Business #4 in the world based on publications in the top 3 Information Systems Journals in the last 15 years. (Journals include Information Systems Research, MIS Quarterly, & Management Science).

The UTD Top 100 World Rankings of Business Schools Based on Research Contribution: 2005–2019 (Top 3 IS Journals)

Rank University Articles Score Country
1 University of Pennsylvania (The Wharton School) 179 88.88 USA
2 University of Texas at Dallas (Naveen Jindal School of Management) 162 85.12 USA
3 New York University (NYU) (Leonard N Stern School of Business) 165 80.12 USA
4 University of Maryland at College Park (Robert H. Smith School of Business) 163 79.95 USA

The Information Systems faculty at the Smith School has a distinguished record of research accomplishments and external visibility. The Information systems faculty’s research interests cover a wide range of application areas including predictive analytics, machine learning, and AI, digital innovations, online platforms & markets, mobile technologies, health-care, business value of technology, and the sharing economy, among others,

The Smith School IS PhD program has an excellent track record of placing students in top-tier business schools and research institutions across the world.

Recent Placements

Mikhail Lysyakov, Assistant Professor, Simon Business School, University of Rochester.
Dissertation Title: Empirical Investigation of Users’ Successful Strategies in Online Platforms: Evidence from Crowd-sourcing and Social Media Platforms.
Sabarirajan Karmegam. Assistant Professor, School of Business, George Mason University.
Dissertation Title: Marriages Made in Silico: Essays on Social Norms, Technology Adoption, and Institutions in Online Matrimonial Matching Platforms
Raveesh K. Mayya. Assistant Professor, Stern School of Business, New York University.
Dissertation Title: Mechanism Designs to Mitigate Disparities in Online Platforms: Evidence from Empirical Studies

Weiguang Wang. Assistant Professor, Simon Business School, University of Rochester.
Dissertation Title: Using Deep Learning to Improve Healthcare Quality and Efficiency

Lanfei Shi. Assistant Professor, McIntire School of Commerce, University of Virginia.
Dissertation Title: Designing Information Strategies for Digital Platforms: Findings from Large-scale Field Experiments.

Dongwon Lee. Assistant Professor, HKUST Business School, HKUST.
Dissertation Title: Essays on Customer Analytics in Mobile Ecosystems.

Yang Pan. Assistant Professor, E.J. Ourso College of Business, LSU.
Dissertation Title: Enemies at the Gate? Essays on New Entry Threats in the U.S. Information Technology Industry.

Tianshu Sun. Assistant Professor, Marshall School of Business, USC.
Dissertation Title: Engineering Digital Sharing Platforms to Create Social Contagion: Evidence from Large-scale Randomized Field Experiments.

Jorge Meijia. Assistant Professor, Kelley School of Business, Indiana University.
Dissertation Title: Vox Populi: Three Essays on the Use of Social Media for Value Creation in Services.

PhD Coursework

PhD students in IS are required to complete at least 42 credits of coursework. Students generally complete their major coursework within their first two years in the program. During the summer after the first year, students work on a summer research project. A paper-based on that project is submitted and presented to the faculty during the Fall of the 2nd year. After completing all relevant coursework, students take a comprehensive exam in the summer of their second year. Following successful completion of the comprehensive exam, students commence work on their dissertation research. The dissertation is an independent research project conducted by the student under supervision of a dissertation committee, assembled by the student. Research interests of the current faculty include technical, behavioral, organizational, and social issues related to information systems. Students may, in their dissertations, choose to pursue any of these avenues.

Major Specification – Required Courses
BMGT 808 D: Information Systems Economics - 1
BMGT 808 E: Information Systems Economics - 2
BMGT 808 I: Quality, Transparency, and Value of Information
BMGT 808 J: Institutions, Firms, and Collectives
BMGT 808 O: Current Topics in IS Research: Research Methods
BMGT 808 P: Current Topics in IS Research: Opportunities at Disciplinary Interfaces
BMGT 808 V: Current Topics in IS Strategy - 1
BMGT 808 W: Current Topics in IS Strategy - 2
BMGT 808 R: Research Seminars

First Minor (Research Methodology) Specification
AREC623: Applied Econometrics I
AREC 624: Applied Econometrics II
BMGT 808 G: Applied Microeconomics

Second Minor Specification
Students must take four additional courses in a minor field. This may be another field within the Smith School (e.g., management, marketing) or from another part of the University (e.g., psychology, computer science, sociology). Courses should generally be at the doctoral level.

Economics Focus:
ECON 603: Microeconomic Analysis I
ECON 604: Microeconomic Analysis II
AREC 815: Behavioral and Experimental Economics
ECON 635: Experimental Economics
ECON 625: Computational Economics

Marketing Focus:
BMGT 858 P: Marketing Models
BMGT 858 J: Structural Models

Strategy Focus:
BMGT 878 L: Limited Asymmetric Information
BMGT 858 X: Best Methods Course Ever, Really
BMGT 858 R: Strategy and Entrepreneurship Research Methods Foundation

Machine Learning Focus:
CMSC 723: Computational Linguistics I
BMGT 726: Machine Learning

Other Requirements
Incoming students are required to attend the Econ Math Camp before the start of their first year and pass the Math Camp exams.
Any student admitted without a sufficient technology background will be required to take at least two technology-related classes and one other MBA-level course. These courses will be determined in consultation with the IS PhD program director.

Admission to Candidacy

To be admitted to candidacy students must successfully complete all coursework (including methods courses, second minor and credits of the DO&IT Seminar), the first year summer paper, and the comprehensive exam.

Recommended Schedule and Milestones for the Information Systems PhD

Year 1, Semester 1:
Applied Microeconomics
Econometric Analysis 1
IS research seminar 1
IS research Seminar 2
Research work with faculty

Year 1, Semester 2:
Econometric Analysis 2
IS research seminar 3
IS research Seminar 4
Work towards a conference publication

Year 1, Summer:
Conduct independent research with faculty advisor
Summer research paper

Year 2, Semester 1:
IS research seminar 5
IS research Seminar 6
Minor Course 1
Minor Course 2
Research work with faculty

Year 2, Semester 2:
IS research seminar 7
IS research Seminar 8
Minor Course 3
Minor Course 4
Prepare to submit journal article by the end of summer.

Year 2, Summer:
Complete Comprehensive Examination

Year 3, Semester 1:
Minor Course 5 (If required)
Methodology Course 4 (if required)
Research presentation in premier academic conferences

Year 3, Semester 2:
Teach an undergraduate/graduate course
Advance to Candidacy

Year 3, Summer:
Begin work on dissertation in consultation with the Academic Advisor

Year 4, Semester 1:
Dissertation Research

Year 4, Semester 2:
Teach an undergraduate/graduate course
Dissertation Proposal defense

Year 4, Summer:
Dissertation Research

Year 5, Semester 1:
Dissertation Research
Prepare for Job Market Interviews at premier conferences – AMCIS, INFORMS, ICIS

Year 5, Semester 2:
Dissertation Research
Campus Interviews and Job Talks

Year 5, Summer:
Dissertation Defense and Graduation


For academic issues, contact:
Prof. Siva Viswanathan
Professor of Information Systems
Coordinator, IS Phd Program
Phone: 301-405-8587

For admission issues, application status, or other questions, please email or call 301-405-2214.

Information On Choosing a Doctoral Program

How should a potential applicant choose among the large number of PhD programs in information systems and related fields? You can find considerable information about doctoral programs on AISNET.

At universities like Maryland, the PhD program concentrates on research, and it is important for you to be excited by the prospects of a career as a researcher when considering doctoral studies. In evaluating schools, the first question is what kind of research does the IS faculty conduct? Are faculty members prominent in the field, are they currently involved in leading-edge research and are they publishing their results? You can learn a great deal from looking at faculty research pages on different schools' websites. You will find that several publications rank Maryland's Information Systems group as one of the top in the world.

Schools have different emphases in their programs, for example, some schools may focus on studying information systems from an economics perspective while others might focus on the more technical aspects. Maryland has a diverse group of IS faculty with interests in managerial, economics, and technical areas.

You also might want to consider the size of the IS faculty; a larger, more diverse faculty can support research in many different areas, giving you a wide choice in dissertation topics.

Location is another consideration, especially if you are interested in field research. A school in a major metropolitan area offers greater access to businesses and potential research sites.

A good way to learn more about a school is to send email to faculty members with questions about the school and their research. You can also gain useful insights by contacting doctoral students who are currently enrolled in the PhD program.

Prof. Siva Viswanathan
Coordinator, IS PhD Program

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