College of Business Administration
Dean, College of Business Administration and
Professor of Management Science
University of Missouri - St. Louis
Keith Womer serves as Dean of the College of Business Administration and Professor of Management Science at the University of Missouri-St. Louis. He has previously served as Director of the Hearin Center for Enterprise Management at the University of Mississippi. He was principal investigator for several research projects funded by the Office of Naval Research, the Air Force Business Management Research office, and other government agencies. He served as Interim Dean of the Ole Miss School of Business Administration for two years. Previously he served as Associate Dean for Faculty and Research and as the chair of the Department of Economics and Finance from 1986 to 1998. Prior to that time he was Professor of Economics and Professor of Management at Clemson University. He has also served on the faculty of the Air Force Institute of Technology and the Naval Postgraduate School. He earned the Ph.D. in Economics from Penn State and a B.A. from Miami University. Dr. Womer has also served as a visiting faculty member at East China Textile University and at the University of Torino.
Dr. Womer has written extensively in the area of cost estimation and project management in the public sector. His book, The Economics of Made-to-Order Production: Theory with Applications Related to the Airframe Industry, coauthored with Thomas Gulledge, summarizes early work in this area. Later papers apply this body of theory to project management and system selection in the Department of Defense and throughout the public sector. Much of this work involves the analysis and estimation of the dynamic systems that result from the attempt to determine the optimal schedule for producing made-to-order systems that are characterized by learning by doing and a fixed time horizon. Recently he has explored the use of Data Envelopment Analysis to aid in system selection. He teaches in the areas of Business Statistics and Operations Management.