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

Lévesque, M., Zhao, X. and J. Bian (2018). "Competitive Interplay of Production Decisions: Rivalry Between Established and Startup Firms", IEEE Transactions on Engineering Management, 65(1), 85-98.

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Abstract This paper's novelty is the modeling of competition in production quantity and product-launch timing, which has been silent regarding the impact of these interdependent decisions on firm survival. We rigorously address the competitive interplay between a startup and an established rival by developing a game-theoretic model that captures the startup's vulnerability to failure through maximizing its survival likelihood. We allow the established rival to behave strategically by anticipating the startup's timing and production decisions prior to making its own production decision. We propose that unless the market-entry investment is low, a survival-maximizing startup should wait to launch its product, and do so with a larger production output than the established rival, when delaying the product launch enables the startup to charge a high price. Insights on the established firm involve the benefit from behaving strategically, which is when competing with either a survival-maximizing or profit-maximizing startup. If the market-entry investment is large, comparing a survival-maximizing startup with a profit-maximizing startup suggests that the former produces at a larger scale than the latter when either startup competes with an established rival, which in turn is forced to reduce its production level.

Saxton, G., Wu, H. and Zhuang, J. (2014). "Publicity vs. Impact in Nonprofit Disclosures and Donor Preferences: A Sequential Game with One Nonprofit Organization and N Donors", Annals of Operations Research, 221, 469-491.

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Abstract Charitable giving is one of the essential tasks of a properly functioning civil society. This task is greatly complicated by the lack of organizational transparency and by the information asymmetries that often exist between organizations and donors in the market for charitable donations. The disclosure of financial, performance, donor-relations, and fundraising-related data is thus an important tool for nonprofit organizations attempting to attract greater donations while boosting accountability and public trust. There are, however, varying payoffs associated with such disclosure depending on the nature of donor preferences and the relative openness and effectiveness of competing organizations. To help understand the interplay between nonprofit organizational disclosures and individual donations, we present a novel game-theoretic model of disclosure–donation interactions that incorporates the predominant forms of both donor preferences and “value-relevant” information.

Lee, I.H., Lévesque, M. and M. Minniti (2012). "Employees’ Break-offs and the Birth of Clusters", IEEE Transactions on Engineering Management, 58(2), 278-292.

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Abstract Empirical observation suggests that several industrial clusters originate from employees who break off and locate their new firms close to former employers. The reasons for such a choice are complex and include a variety of costs' considerations. We present a two-player three-stage simultaneous game with interdependent decisions concerning break-offs, deterrent compensations, location, and profit-maximizing production outputs. The structure of the game explains under what conditions a break-off is desirable, what location's choice makes it optimal, and why the break-off process may lead to the birth of a cluster. We demonstrate how marginal production/congestion cost, degree of product differentiation, R&D investment in a region, and market size, all influence the likelihood of a firm's break-off and its subsequent location decision. Our results provide a rationale for why, in industries in which technology plays a significant role, an increase in R&D investment in the region may encourage the break-off firm to locate away from the incumbent. We also show that subsidies aimed at increasing manufacturing activities and diffusing commercializable innovations can be ineffective in promoting clustering and unnecessary in larger markets, and their exact size is crucial in determining their effectiveness.