Michael Ketzenberg
- mketzenberg@tamu.edu
- 979-845-9541
- Wehner 320H
Education
PhD, University of North Carolina, Chapel HillMBA, Vanderbilt University
BS, Carnegie Mellon University
Biography
Michael Ketzenberg is a Professor of Information and Operations Management at the Mays Business School at Texas A&M University and also holds a courtesy appointment with the Department of Finance. His research falls under the umbrella of supply chain management and focuses on the value and use of information for inventory management and management of closed loop supply chains, with significant overlap between the two. Michael also has broad interest in data analytics, with particular emphasis on machine learning applications in the area of FinTech. Dr. Ketzenberg’s research work has been published in several academic journals, among them, Harvard Business Review, Production and Operations Management, Management Science, European Journal of Operational Research, and Journal of Operations Management.
Prior to joining the Mays faculty, Professor Ketzenberg taught for six years at Colorado State University and for one year at George Mason University. He has over eight years of professional work experience as a project manager and systems developer.
Research Publications
Abbey, J. (2018, July 23). A more profitable approach to product returns. Retrieved from https://sloanreview.mit.edu/article/a-more-profitable-approach-to-product-returns/
Choi, S., & Ketzenberg, M. (2018). An inverse newsvendor model to set the optimal number of customers in a capacitated environment. International Journal of Production Economics, 196, 188–197. https://doi.org/10.1016/j.ijpe.2017.11.017
Ertekin, N., Ketzenberg, M., & Heim, G. R. (2019). Assessing impacts of store and salesperson dimensions of retail service quality on consumer returns. Production and Operations Management, 29(5), 1232–1255. https://doi.org/10.1111/poms.13077
Ketzenberg, M., Gaukler, G. M., & Salin, V. (2018). Expiration dates and order quantities for perishables. European Journal of Operational Research, 266(2), 569–584. https://doi.org/10.1016/j.ejor.2017.10.005