416-736-2100 ext. 33573
Area(s) of Expertise
- Business Analytics
- Demand Fulfilment Analytics
- Operational Performance Analysis
- Operations Management
- Optimization Under Uncertainty
About Isik Bicer
Dr. Isik Bicer is an Assistant Professor of Operations Management at the Schulich School of Management, York University. His current research focuses on analyzing the impact of operational factors on financial parameters (e.g., stock price, capital structure, and return on assets) and designing operational strategies to ensure high customer-fulfillment rates in economically feasible ways. He uses methods from corporate finance, quantitative finance, and optimization theory to address these challenges. His research has appeared in the Financial Times listed journals such as Production and Operations Management and the Journal of Operations Management. He is also a member of Editorial Review Board of the Journal of Operations Management.
Prior to joining the Schulich School of Management, he was a faculty member at the Rotterdam School of Management, Erasmus University, the Netherlands; a postdoctoral researcher at the Swiss Federal Institute of Technology (EPFL), Switzerland. During his doctoral studies, he was a member of the OpLab team at the University of Lausanne, Switzerland and collaborated with the US Department of Commerce for the development of a cost assessment tool. He also has an industry experience in pharmaceutical and finance industries. Before moving to Canada, Dr. Bicer has worked and lived in the Netherlands, Switzerland, and Turkey.
Bicer, I., Hagspiel, V., De Treville, S. (2018), Valuing supply-chain responsiveness under demand shocks, Journal of Operations Management, 61, 46-67
Bicer, I., Seifert, R. W. (2017), Optimal dynamic order scheduling under capacity constraints given demand-forecast evolution, Production and Operations Management, 26(12), 2266-2286
De Treville, S., Bicer, I., Chavez-Demoulin, V., Hagspiel, V., Schurhoﬀ, N., Tasserit, C., and Wager, S. (2014), Valuing lead time, Journal of Operations Management, 32(6), 337-346