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

Kozlova, M. and Yeomans, J.S. (2022). "Extending Simulation Decomposition Analysis into Systemic Risk Planning for Domino-Like Cascading Effects in Environmental Systems", Journal of Environmental Informatics Letters , 7(2), 64-68.

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Abstract In interconnected environmental systems, the innocuous failure of one component can sometimes trigger a subsequent domino-like effect resulting in a cascading collapse of the entire system. Risk analysis in “real world” contexts frequently requires the need to simultaneously contrast numerous uncertain factors and difficult-to-capture dimensions. Monte Carlo simulation modelling has often been employed to integrate uncertain inputs and to construct probability distributions of the resulting outputs. Visual analytics and data visualization can be used to support the processing, analyzing, and communicating of the influence of multi-variable uncertainties on the decision-making process. In this paper, the novel Simulation Decomposition (SimDec) analytical technique is extended into complex assessments of cascading risk analysis and used to quantitatively examine situations involving potentially catastrophic, domino-like collapses of an entire system. SimDec analysis proves to be beneficial due to its ability to reveal interdependencies in complex models, its ease of decision-maker perception, its visualizable analytic capabilities, and its significantly lower computational burdens. The case example visually demonstrates that when a system collapse is a low-probability/high-impact event, more expensive, reactive policies minimize the overall value loss under conditions of system survival, while more proactive policies enable better loss prevention under system survival. However, proactive approaches significantly decrease the likelihoods and magnitudes of losses for scenarios resulting from the collapse of the system. Such findings would not have been revealed without the visualization provided by SimDec.  

Cui, Y., Geobey, S., Weber, O., & Lin, H. (2018). "The Impact of Green Lending on Credit Risk in China", Sustainability, 10(6), 2008.

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Abstract This study explores China’s green credit policy from a credit risk perspective. Green finance has been growing rapidly in China since the government issued its Green Credit Policy. The objective of this study is to explore whether green loans are less risky than non-green loans. Based on a five-year dataset of 24 Chinese banks, we used panel regression techniques, including two-stage least square regression analysis and random-effect panel regression to examine whether a higher green credit ratio reduces a bank’s non-performing loan ratio (NPL ratio). The results suggest that allocating more green loans to the total loan portfolio does reduce a bank’s NPL ratio. We conclude that institutional pressure by the Chinese Green Credit Policy has a positive effect on both the environmental and the financial performance of banks. The study contributes to the literature on the correlation between green lending and credit risks, as well as to the literature on the impact of institutional pressure on environmental and financial risks.