Welcome to the new Schulich Peer-Reviewed Publication Database!
The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:
- Faculty Member’s Name;
- Area of Expertise;
- Whether the Publication is Open-Access (free for public download);
- Journal Name; and
- Date Range.
At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.
If you have any questions or input, please don’t hesitate to get in touch.
De Treville, S., Bicer, I. and Hagspiel V. (2018). "Valuing Supply-Chain Responsiveness Under Demand Shocks", Journal of Operations Management, 61(1), 46-67.
AbstractAs the time between the decision about what to produce and the moment when demand is observed (the decision lead time) increases, the demand forecast becomes more uncertain. Uncertainty can increase gradually in decision lead time, or can increase as a dramatic change in median demand. Whether the forecast evolves gradually or in jumps has important implications for the value of responsiveness, which we model as the cost premium worth paying to reduce the decision lead time (the justified cost premium). Demand uncertainty arising from jumps rather than from constant volatility increases the justified cost premium when an average jump increases median demand, but decreases the justified cost premium when an average jump decreases median demand. We fit our model to two data sets, first publicly available demand data from Reebok, then point‐of‐sale data from a supermarket chain. Finally, we present two special cases of the model, one covering a sudden loss of demand, and the other a one‐time adjustment to median demand.
Bicer, I. and Seifert, R.W. (2017). "Investments in Lead-Time Reduction: How to Finance and How to Implement", Foundations and Trends in Technology, Information and Operations Managemen, 11(1-2), 32-45.
AbstractWe consider a multi-period production problem in which a manufacturing firm produces a seasonal product to satisfy uncertain market demand in each selling period. The firm jointly determines the production quantity, working capital level, the amount of short-term debt, and dividends paid out to equity holders. It also has an option to raise capital by issuing long-term debt and invest in reducing lead times. Demand forecasts are updated according to a multiplicative martingale process. We formalize the problem by developing a Markov Decision Process (MDP) and characterize the structure of the optimal policy, which allows us to solve the problem in polynomial time. We show that debt (equity) financing is more beneficial for the products with low (high) demand uncertainty. Using our model, we propose a simple typology that shows effective investment strategies in reducing the lead time depending on demand uncertainty and the value added by production of each sub-component.
Bicer, I. and Hagspiel, V. (2016). "Valuing Quantity Flexibility Under Supply Chain Disintermediation Risk", International Journal of Production Economics, 180, 1-15.