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

Liddle, B. and Sadorsky, P. (2020). "How Much Do Asymmetric Changes in Income and Energy Prices Affect Energy Demand?", The Journal of Economic Asymmetries, 21.

View Paper

Keywords
Abstract This paper uses a large unique panel data set of 91 OECD and non-OECD countries and recently developed panel regression estimation techniques to answer the question by how much energy demand changes when income and energy prices display asymmetric effects. Both long run and short run impacts are studied. For the full sample, we find the short run impact of a 1% increase in GDP increases energy consumption by 0.35% while a 1% decrease in GDP decreases energy consumption by 0.68%. These values are similar across different country groupings. GDP decreases have a larger impact on energy consumption than increases in GDP by a factor of approximately 2 to 1. We do not, however, find any evidence of asymmetric long run GDP effects. The result that energy demand falls more proportionally when GDP falls then when GDP rises has implications for energy policy and energy demand forecasting. There is evidence of long run price asymmetry for the OECD countries.

Day, J., Kristal, M., Pathak, S. and Sawaya, W. (2015). "Sensing Abnormal Resource Flow Using Adaptive Limit Process Charts in a Complex Supply Network", Decision Sciences, 46(5), 961–979.

View Paper

Keywords
Abstract Supply networks are becoming increasingly complex with multiple overlapping relationships between firms that may span across industries. Consequently, inventory management is becoming more difficult as managers have to cope with variability in the supply flows that originate from different parts of the network. Managers that quickly sense abnormal flows may intervene and adapt their inventory policies in response to system changes. In this article, we present a framework for sensing abnormal flows originating within the upstream supply network of a focal organization. Our framework combines time series modeling with process charts to identify abnormal flow patterns in the incoming supply streams. It is a flexible framework that uses off‐the‐shelf technology to provide managers with a process that can be employed for monitoring multiple individual or aggregated data streams originating within any complex system such as complex adaptive supply networks. We illustrate our framework on four years of longitudinal supply data from the second largest food bank in the United States. We identify multiple instances of abnormal supply flows and validate our results through rigorous inventory analysis as well as field‐based expert interviews. We discuss the implications of our findings for inventory management in complex supply networks, both from academic and practitioner points of view.