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

Geissler, B., Mew, M. C., Weber, O., & Steiner, G. (2015). "Efficiency Performance of the World’s Leading Corporations in Phosphate Rock Mining", Resources, Conservation and Recycling, 105, Part B, 246-258.

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Abstract The prominence of phosphorus (P) is represented by three major aspects: first and most important, P is essential for all life on Earth; second, no other element or substance can act as a substitute for P; and third, P is considered a non-renewable resource and thus finite. In regard to global food security and P as one of the three major macronutrients, the world faces an extensive challenge to utilize this finite and unsubstitutable commodity in the most effective as well as the most efficient way. Efficiency in general has increasingly become of major importance over the last several decades, especially within competitive commodities. Practically all PR used for chemical fertilizers originates from exploitable deposits that are concentrated in a rather small number of countries and mined vastly by only a limited number of global enterprises. Whereas these enterprises differ in factors such as size, vertical and horizontal integration, legal form, or type of ownership, their overall goal as corporations remains the same-the optimization of their operations. Consequently, firms can strive to (a) minimize their inputs at constant output levels; (b) maximize their outputs at constant input levels; or (c) increase their efficiency ratio by adjusting inputs and outputs at the same time. In contrast to the oil industry, the PR market is demand driven, which means that not everything that could be produced is immediately consumed. This study attempts to measure, compare, and analyze the technical efficiency performance of the major global corporations involved in PR mining by using the BCC (Banker, Charnes, and Cooper) and CCR (Charnes, Cooper, and Rhodes) models of data envelopment analysis. The analysis includes total technical efficiency as well as the disaggregated pure technical and scale efficiency and a breakdown of the factors accounting for inefficiency. The 24 firms included in the analysis account for 67.3% of the global phosphate rock ore capacity and 61.4% of phosphate rock concentrate capacity. Based on the BCC and CCR modeling a higher percentage (36% vs. 20% – Model 1; 36% vs. 10% – Model 2) of publicly quoted companies (such as PotashCorp) are classified as efficient compared to state-owned companies (such as OCP). However, the frequencies of efficiency performance do not differ in such a way that a Fisher Exact Test would suggest statistical significance for these data. This indicates that general assumptions regarding the different strategies of state-owned and publicly quoted firms are not necessarily valid.

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

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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.