Publications Database

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.

 

Search Results

De Treville, S., Bicer, I. and Hagspiel V. (2018). "Valuing Supply-Chain Responsiveness Under Demand Shocks", Journal of Operations Management, 61(1), 46-67.

Open Access Download

Abstract As 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.

Open Access Download

Abstract We 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.

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Abstract We consider a supply chain with one supplier and one retailer in which the parties develop a quantity flexibility contract to specify the conditions of procurement activities. The contract allows the retailer to adjust the initial order quantity after the partial or full resolution of demand uncertainty, which helps the retailer reduce supply–demand mismatches. We use the multiplicative martingale model of forecast evolution to analyze the impact of lead-time reduction on the value of quantity flexibility for the retailer. We find that the shorter the lead time, the higher the value of quantity flexibility. Quantity flexibility may, however, also cause supply chain disintermediation problems for the retailer, such as the supplier bypassing the retailer and selling its products directly to end customers. We incorporate the “contracts as reference points” theory into our quantity flexibility contract model to capture the impact of supply chain disintermediation on the retailer's profit. This approach allows us to analyze the trade-off between decreasing supply–demand mismatches and increasing supply chain disintermediation problems. We show that the impact of lead-time reduction on decreasing the disintermediation risk highly depends on the critical fractile. We also find that the supplier's cost structure has a significant effect on the trade-off. When the supplier's initial investment cost is relatively low, the disintermediation problems become less important.