Business Analytics
Business Analytics PH.D.
The University of Tennessee’s Ph.D. in Business Analytics program is designed for ambitious scholars seeking to make a profound impact in academia, industry and policy. With a focus on rigorous training in theory, methods and cutting-edge research, our program prepares students to tackle complex global challenges. Join a community of dedicated faculty and peers committed to advancing knowledge and shaping the future.
Business Analytics
PH.D. Faculty
The Department of Business Analytics has 18 research-active tenured or tenure-track faculty, with recent publications in top-tier journals, including Management Science, Marketing Science, IEEE Transactions on Knowledge and Data Engineering, Information Systems Research, INFORMS Journal on Applied Analytics, INFORMS Journal on Computing, Journal of the American Statistical Association, Journal of Marketing, Journal of Operations Management, Manufacturing & Service Operations Management, Production and Operations Management, Statistica Sinica and Technometrics. To find out more about each faculty research areas, please review the department faculty page.
Research Interests: Developing effective and scalable algorithms for identifying patterns and effects in large-scale and/or unstructured data.
Business Analytics
Foundation Course Faculty
- Emre Demirkaya, Assistant Professor, Roy & Audry Fancher Faculty Fellow
Research Interests: Focuses on high-dimensional statistics, big data problems and statistical machine learning including variable selection, FDR control and model selection. - Chuanren (Charles) Liu, Associate Professor, Beaman Professor in Business, Sampson Enterprises Faculty Fellow
Research Interests: Data-driven research methodology and applications in healthcare, e-commerce and investment. - Yuanyang (Yang) Liu, Assistant Professor
Research Interests: Applying data science techniques to study labor market and HR analytics questions. - Tingliang Huang, Amazon Distinguished Professor of Business Analytics, Analytics Ph.D. Program Recruiting Lead
Research Interests: Business analytics, operations-marketing interface, supply chain management, service operations, innovation and sustainable operations.
Business Analytics PH.D.
Admissions
The program admits three to four students each fall. All interested students must apply online through the university’s graduate admissions office. The following items are required for submission:
- Preferred Background: Strong math background, including calculus and statistics
- GPA: Ideal undergraduate GPA 3.6 or higher
- GRE/GMAT: Ideal GRE score: 80th percentile or higher
- English Language Proficiency: Applicants whose native language is not English must take the TOEFL/IELTS. The TOEFL and IELTS scores are valid for two years from the date they are taken
- Statement of Purpose: Required
Business Analytics PH.D.
Frequently Asked Questions
How do I apply to your graduate program?
Apply through the official Graduate School Application.
When is the deadline to apply?
We begin accepting applications for fall in September, as soon as the application system opens. Preference will be given to applications received before December 1. The Graduate Admissions Committee begins reviewing applications at that time. The University of Tennessee has rolling admissions, so applications received after December 1 are still reviewed. Keep in mind that for international students, the final deadline to apply is February 1.
When is the deadline for spring admission?
We only admit in the fall semester each year. Spring admissions are considered only in extreme circumstances.
Can you waive my application fee?
At this time, we are unable to cover the costs to the university by waiving application fees.
Do I need to contact the faculty I wish to work with before applying?
No, it is not necessary to contact faculty before applying. We ask that you identify in your personal statement faculty members that you might want to work with based on their research. This helps the committee better understand your interests. Please refer to our faculty websites for their research interests/areas before writing your personal statement: BAS Faculty
Is the GRE required?
The GRE or GMAT is required, and official scores must be included in your application materials.
(International Students) What TOEFL or IELTS scores are required?
The program follows the Graduate School’s standard testing requirements for English language proficiency. Please refer to that page for current minimum scores, accepted tests and score submission instructions.
What code should I use for UT on the IELTS and other standardized tests?
The UT code is 1843.
My official transcripts are costly and/or difficult to obtain. Do I have to submit official transcripts?
For application review, a scanned PDF of your transcript is acceptable. If you are accepted into the program, official transcripts from the colleges you attended will be required as a condition of admittance.
Do I have to have my transcripts translated into English?
It is difficult for the committee to assess your transcripts if they are not translated, so translation will be necessary.
How competitive is my application?
Because a new pool of applicants applies each year, and applicants are being evaluated based on the current pool, it is not possible to answer such questions ahead of the official process.
Where do I apply for GTA/GRA assistantships?
At this time, all admitted Ph.D. students in Business Analytics Students are automatically assigned a GTA/GRA in their offer letters. An application is not required. We only fund around three or four students each admissions cycle. Each of those students receives four years of funding, including a stipend and tuition waiver. The funded student works in the department 20 hours per week.
Do students receive a stipend?
Admitted students on GTA/GRA assistantships receive a monthly stipend, a tuition waiver and healthcare coverage. Students are responsible for some university fees.
I applied weeks ago and want to know the status of my application.
The Ph.D. in Business Analytics Admissions Committee does not begin reviewing applications until after December 1. After December 1, all applications are reviewed, and then decisions are made based on funding and space availability. Given the number of applications and the amount of material they contain, this can take some time. Decisions on all applications are usually completed by April 15. You will receive a letter when decisions are completed. Please keep in mind that the Admissions Committee cannot evaluate your application if it is incomplete.
Can I do this program online?
No, the entire program must be completed in person, on campus.
How will I know the committee’s decision?
Someone from the committee will first reach out to you for an interview if your file is competitive for admission. At a later date, after the interview has taken place, you will be notified via email if you have been admitted to the program.
What else should I know before applying?
The Ph.D. program aims to prepare students for faculty positions at leading business schools. A strong commitment to research and a clear interest in pursuing an academic career are essential. Key strengths and distinctive features of the Ph.D. program include:
BAS faculty hold prominent leadership positions in their fields and include department, senior and associate editors in leading academic journals, such as Production and Operations Management, Decision Sciences, Service Sciences, Naval Research Logistics, INFORMS Journal on Data Science and INFORMS Journal on Applied Analytics. Faculty also include past or current presidents and vice presidents of POMS College of Sustainable Operations, College of Supply Chain Management, INFORMS College on AI and an American Statistical Association Fellow.
BAS’s 18 tenured or tenure-track faculty members with expertise cover various areas of business analytics, including operations management, data science, AI, machine learning, marketing science, supply chain management and statistics.
BAS faculty are productive, leading scholars, publishing regularly in top academic journals in their fields. The BAS research group is ranked #4 in in North America for number of articles published in Manufacturing & Service Operations Management, Production and Operations Management and Journal of Operations Management from 2023-2026 (according to the UTD Top 100 Business School Research Rankings).
Business Analytics PH.D.
Academic Information
The Ph.D. in Business Analytics has five learning objectives aimed at training candidates to perform research consistent with the college’s mission to generate nationally and internationally recognized outcomes that improve the world.
- Clearly communicate research findings and be able to present work at national and international conferences.
- Gain deep knowledge of the literature and developments in a specific area within analytics in order to further the field’s appropriate methodological tools.
- Fulfill the growing need for faculty that can teach business analytics at the undergraduate and graduate levels.
- Conduct research that addresses real-world problems using quantitative and methodological models to visualize and interpret data.
- Develop and test research hypotheses by acquiring data from primary and secondary sources.
Coursework
The Ph.D. in Business Analytics requires 48 credit hours of coursework, excluding dissertation hours.
- BZAN 615 – Statistical Learning
Focuses on statistical models for supervised learning problems. The course covers linear methods for regression and classification. Model selection, bias-variance tradeoff, subset selection and shrinkage methods are discussed. - BZAN 620 – Applied Optimization and Data Analytics
Applied optimization is a core and central stream in data mining, machine learning, operations research and management science. This course presents modeling techniques in optimization and data analytics, focusing on problem formulations and solutions in applying data-intensive optimization techniques for research and application problems in a sufficiently broad domain.
- BZAN 643 – Data Science for Business Research
Presents recent development in data science techniques and their applications in current business research. Topics include causal inference with machine learning, text as data and network analysis. The course demonstrates the importance and opportunities of combining new data sources and data analytics methodologies to generate business insights. - BZAN 645 – Machine Learning
Topics in Machine Learning and Artificial Intelligence that are relevant for solving business problems. This course covers supervised learning methods (such as classification and regression trees and artificial neural networks), unsupervised learning methods (e.g., cluster analysis and dimension reduction) and semi-supervised learning.
The four core courses listed above provide a solid foundation in data and analytics. Beyond that, you are free to specialize in your research domain with your Ph.D. Advisor’s guidance. You have flexibility to customize your doctoral coursework.
Elective Courses
In consultation with their advisor, students customize their remaining doctoral coursework offered either by the Business Analytics department, or other departments including Computer Science, Economics, Industrial Engineering and Mathematics.