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

V. Dhingra, Govind Kumawat, Debjit Roy, and René de Koster (2018). "Solving Semi-Open Queuing Networks with Time-Varying Arrivals: An Application in Container Terminal Landside Operations", European Journal of Operational Research, 267(3), 855-876.

View Paper

Abstract Semi-open queuing networks (SOQNs) are widely applied to measure the performance of manufacturing, logistics, communications, restaurant, and health care systems. Many of these systems observe variability in the customer arrival rate. Therefore, solution methods, which are developed for SOQNs with time-homogeneous arrival rate, are insufficient to evaluate the performance of systems which observe time-varying arrivals. This paper presents an efficient solution approach for SOQNs with time-varying arrivals. We use a Markov-modulated Poisson Process to characterize variability in the arrival rate and develop a matrix-geometric method (MGM)-based approach to solve the network. The solution method is validated through extensive numerical experiments. Further, we develop a stochastic model of the landside operations at an automated container terminal with time-varying truck arrivals and evaluate using the MGM-based approach. Results show that commonly used time-homogeneous approximation of time-varying truck arrivals is inaccurate (error is more than 15% in expected waiting time and expected number of trucks waiting outside the terminal) for performance evaluation of the landside operations. The application results are insightful in resource planning, demand leveling, and regulating the number of trucks permitted inside the terminal.

Goldsby, T.J., Knemeyer, A.M., Miller, J., Saldanha, J.P. and Rungtusanatham, M. (2018). "How Does Electronic Monitoring Affect Hours-of-Service Compliance?", Transportation Journal, 57(4), 329-364.

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Abstract Accidents involving large commercial trucks kill over 3,000 motorists every year in the United States. A substantial number of these accidents stem from truck drivers operating their trucks while excessively fatigued. This concern has resulted in regulatory agencies establishing hours-of-service (HOS) rules that carriers must ensure their drivers abide by. In this study we examine the relationship between carriers' capability at monitoring their truck drivers using electronic technologies and carrier-level compliance with HOS rules. Drawing on principles from deterrence theory, we explain why this relationship should be sigmoidal (S-shaped) in nature such that motor carriers receive the greatest gains from investing in electronic monitoring capability when they have a moderate level of this capability. We subject our theorized prediction to empirical testing using a longitudinal research design that combines primary data on motor carriers' electronic monitoring capability and secondary data from regulators regarding carrier-level compliance with HOS rules. Results from our econometric analysis corroborate the hypothesized sigmoidal relationship, which stands up to stringent robustness testing. These results hold important implications for theory and practice.