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

Cook, W., Li, W., Li, Z. and Zhu, J. (Forthcoming). "Efficiency Measurement for Hierarchical Situations", Journal of the Operational Research Society.

Open Access Download

Abstract The measurement and monitoring of the efficiency of processes in organisations has become an important undertaking in today’s competitive environment. A fundamental tool for this undertaking is data envelopment analysis (DEA). The conventional setting for DEA views the decision-making unit (DMU) (school, hospital etc.) as a black box with inputs entering and outputs leaving. The current paper looks at a problem setting somewhat related to a multistage situation but pertaining to a particular form of hierarchical structure. Specifically, we examine a set of electric power units that act as sub-units or sub-DMUs, operating under the framework of set of power plants that play the role of DMUs. We develop a DEA-like methodology that evaluates, in a two-stage manner, both the efficiencies of the sub-units and of the aggregates of those sub-units (the plants). In so doing, the approach attempts to have the projected values of plant-level inputs and outputs match up with the corresponding aggregate values of the sub-unit projections, as is the case prior to projection to the frontier. Since such projections may in fact not match up as described, we introduce a goal-DEA methodology to minimise the extent of any failure to achieve this match up.