New Schulich Faculty Isik Bicer
I S I K B IC E R Assistant Professor of Operations Management and Information Systems
Research Interests • Supply Chain Analytics • Uncertainty Modelling • Optimization Under Uncertainty
Isik is Assistant Professor of Operations Management and Information Systems. Prior to joining the Schulich School of Business, he was a faculty member at the Rotterdam School of Management of Erasmus University in the Netherlands. He holds a PhD degree in Operations Management from the University of Lausanne, Switzerland. Isik’s research focuses on supply chain analytics and supply chain finance. He uses methods from quantitative finance, optimization theory, statistics, and stochastic modelling to develop supply chain models that aim to reduce the mismatches between supply and demand. He also carries out research to improve the financial sustainability of companies by focusing on the effective deployment of supply chain finance tools. His research appeared in the top operations management journals, such as Production and Operations Management and Journal of Operations Management, and some practitioner outlets such as Harvard Business Review and Forbes. The analytical tools developed as the outcome of his research have been implemented in companies in the pharmaceutical, automotive, consumer packaged goods, and agriculture industries. Isik brings a new approach to the supply chain analytics field by modelling the uncertainty. Digital transformation of operations includes two main analytical components: (1) Predictive analytics and (2) Prescriptive analytics. The predictive analytics component aims to forecast demand values in future. This information is later used in the prescriptive analytics component to improve the operational decisions of supply chain executives. The way the data is collected for demand forecasting is subject to some inefficiencies, such that important information is lost due to data aggregation. Isik uses some advanced analytical methods, such as the Fast Fourier Transform, to avoid the loss of information. He strongly believes that if the loss of information is avoided in the predictive analytics models, the value of analytical applications in supply chains would be magnified. Please see his recent publication at HBR for more information about this approach and its successful application in a company: https://hbr.org/2022/01/using-uncertainty-modeling-tobetter-predict-demand.
Alexander Coutts
A L EXA N D E R CO UTTS Assistant Professor of Economics
Research Interests • Behavioural Economics • Development Economics • Experimental Economics
58 Schulich School of Business
Alexander Coutts is Assistant Professor of Economics. His primary area of research is behavioural economics, using field and lab experiments to understand broad interactions between information, beliefs, and behaviour. His research has been published in journals such as American Economic Review, Experimental Economics, Games and Economic Behavior, and the Journal of Development Economics. During his PhD at New York University, he specialized in experimental economics (studying the role of optimism and overconfidence in belief-updating) and development economics (studying patterns of cooperation in rural villages). In addition to his PhD, Alexander holds an MA from Queen’s University and a BA from the University of British Columbia. Prior to joining Schulich, he was a faculty member at the Nova School of Business and Economics (Portugal). There, he worked with the NOVAFRICA knowledge center, utilizing randomized controlled trials (RCTs) to investigate how information affects beliefs and behaviour in the context of the political resource curse in Mozambique and health in Guinea-Bissau. In ongoing research, Alexander studies motivated beliefs, and how belief formation and updating may lead to overconfidence, optimism, and discrimination. In a current project recently funded by SSHRC, he focuses on applying principles from behavioural economics and psychology to study awareness about racial bias. In other ongoing work, he focuses on attribution biases in how individuals update their beliefs about performance when there are other factors to potentially blame. A final related strand of research involves studying gender bias in feedback and attribution. All of this research is made possible through the work of outstanding co-authors working at several different universities. Alexander has taught a wide range of courses including microeconomics, game theory, behavioural economics, and development economics. He enjoys teaching at different levels, from undergraduate to doctoral, and has experience teaching to audiences in different fields: economics, finance, management, law, and general business.
