PhD in Operations, Business Analytics, and Information Systems
The University of Cincinnati Department of Operations, Business Analytics and Information Systems (OBAIS) seeks exceptional students with interest in a wide range of research topics who seek careers as academic researchers, including university professors or applied researchers in academic settings such as research hospitals or public labs and research institutions.
The department's PhD program admits students into its three disciplines, but our students often work on multi-disciplinary problems with both our OBAIS faculty and with faculty from other areas.
- Business Analytics focuses primarily on three methodological aspects of analytics: applied statistics, simulation, and optimization and decision analysis. Our faculty develop, improve, and apply cutting-edge statistical, simulation, and optimization methods such as data mining, longitudinal and nonparametric analysis, discrete-event and agent-based computer simulation, integer programming, and stochastic optimization to a wide variety of problems and industries.
- Information Systems focuses primarily on behavioral and technical/computational issues. Lindner's Information Systems faculty members research topics related to how humans adopt, use, and adapt to technology, how organizational software can use information more effectively, and how databases and other technical systems might be improved, automated, or deployed more effectively.
- Operations Management focuses on research into how production and service systems transform inputs into outputs. This includes a diverse set of topics, such as inventory and supply chain management, transportation networks, service operations, quality, healthcare delivery systems, operations strategy, and developing policies and processes for matching capacity with demand.
OBAIS PhD graduates have been highly successful in both academic and academic-style industrial positions. Our course work includes mathematical programming, stochastic models, and applied statistics along with seminars on the latest developments in the field. Our students are encouraged to take courses from across the University of Cincinnati that combine to best meet their unique educational goals.
While each student enters with a unique background, a typical sequence of matriculation is as follows:
First, our students take 18-24 months of coursework in order to learn advanced research methods as well as deep topical content, such as fundamental concepts and contemporary theory, in their fields.
During the second year of their study, our students undertake the second-year paper, which is usually each student's first attempt at executing a scientific research project from start to finish. This is done under the close supervision of one or more of our faculty advisors.
After all the coursework is completed, our students sit for the written portion of their comprehensive exams. This often occurs during the summer after their second year of classes. The oral portion of the comprehensive exam is to present the second-year paper. This step typically happens within a few months of the written exam. Upon passing the comprehensive exam, our PhD students enter into candidacy and each student begins working on his or her dissertation.
The dissertation is a large work of original research performed primarily by the PhD student with guidance from his or her dissertation chairperson and committee. Typically, between six and 15 months into the dissertation work, students defend their dissertation proposals, which describe the work being carried out, before their committees. Then, upon completion of the dissertation work, students defend their dissertations, again in front of the committee. The dissertation work normally takes two to three years, making the entire program typically require four to five years of full-time work. The OBAIS department does not accept part-time doctoral students.
Each PhD student in Operations, Business Analytics, and Information Systems works individually and closely with a faculty advisor to develop a personalized curriculum uniquely suited to help him or her learn the methods and core knowledge needed to begin a productive and rewarding research career. No two students' research interests are identical so, within the overall structure of the Lindner College of Business PhD program, we seek to customize our doctoral students' programs of courses and matriculation schedules in order to best meet their individual needs and aspirations.
Our academic environment is collegial, engaging, dynamic, and supportive. Those who commit to their doctoral studies will find an extensive and dedicated community to help ensure their academic and professional success. From our cohort of PhD students to intellectually engaged faculty to helpful staff, the community works together to foster student success.
Many of our faculty are leaders in their respective research fields. They have published extensively in peer-reviewed, scientific journals, have won awards for their research and graduate-student teaching and have been invited to serve on the boards of key academic professional societies. They also author industry-leading textbooks and engaged with industry to support businesses' use of analytics and advanced research methods to solve real-world problems. Because of this vigorous intellectual and community engagement, the OBAIS department has been recognized as one of the university's Centers of Excellence through the State of Ohio Academic Excellence Program.
The city of Cincinnati is a metropolitan hub that is home to more Fortune 500 companies per capita than New York, Chicago, or Los Angeles. Seven Fortune 500 companies have their global headquarters located less than three miles from the University of Cincinnati's campus. The city is home to vibrant entertainment and cultural opportunities and offers a variety of affordable living options.
Recent graduates of Lindner's PhD in Operations, Business Analytics, and Information Systems program have accepted positions at:
- Drexel University
- Elon University
- Ivey Business School
- Johns Hopkins University
- Kansas University
- Lehigh University
- McGill University
- Miami University
- Michigan State University
- Stevens Institute of Technology
- Towson University
- University of Dayton
- University of Louisville
- Xavier University
Names of Lindner faculty appear in bold. Names of Lindner PhD candidates are underlined.
Li, S., Zhu, X., Chen, Y., & Liu, D. (2021) “PAsso: an R Package for Assessing Partial Association between Ordinal Variables” (Accepted by The R Journal).
Rea, David, Craig Froehle, Suzanne Masterson, Brian Stettler, Greg Fermann, Arthur Pancioli, (2021) "Unequal but Fair: Incorporating Distributive Justice in Operational Allocation Models," Production and Operations Management, 30(7), 2304-2320.
Green Brittany, Lian Heng, Yan Yu, Tianhai Zu. (2021). “Ultra high‐dimensional semiparametric longitudinal data analysis”, Biometrics, 77(3), 903-913.
Li Z, Wang S, Li W, Zhu T, Fan Z, Xie X., (2021). “Droplet dynamics in a proton exchange membrane fuel cell flow field design with 3D geometry”, International Journal of Hydrogen Energy, 46(31),16693-16707.
Jablokow, K. W., Zhu, X., & Matson, J. V. (2020). “Exploring the diversity of creative prototyping in a global online learning environment”, International Journal of Design Creativity and Innovation, 8(2).
Schneider, M. J., Jagpal, S., Gupta, S., Li, S., and Yu, Y. (2018). A Flexible Method for Protecting Marketing Data: An Application to Point-of-Sale Data", Marketing Science, 37(1), 153-171.
Windeler, J., Chudoba, K., and Sundrup, R. (2017). Getting Away from Them All: Managing Exhaustion from Social Interaction with Telework. Journal of Organizational Behavior, 38(7): 977-995.
Sundrup, R., Froehle, C., & Windeler, J. (2017). Evaluating Effects of Information Incongruence and Gender on Online Review Helpfulness. Proceedings of the 23th Americas Conference on Information Systems, August 10-12, 2017, Boston, Massachusetts, USA.
Schneider, M. J., Jagpal, S., Gupta, S., Li, S., and Yu, Y. (2017). Protecting Customer Data: Marketing with Second-Party Data, International Journal of Research in Marketing, 34(3), 593-603.